diff --git a/api/models/efp_schemas.py b/api/models/efp_schemas.py index 4bcbdd2..4f12396 100644 --- a/api/models/efp_schemas.py +++ b/api/models/efp_schemas.py @@ -181,7 +181,7 @@ def _schema(species: str, charset: str = "latin1") -> DatabaseSpec: ("root_Schaefer_lab", "root Schaefer lab"), ("rpatel", "rpatel"), ("seed_db", "seed db"), - ("seedcoat", "oat"), + ("seedcoat", "arabidopsis seedcoat"), ("selaginella", "selaginella"), ("shoot_apex", "arabidopsis"), ("silique", "arabidopsis"), diff --git a/api/resources/gene_expression.py b/api/resources/gene_expression.py index d777e3e..9f95949 100644 --- a/api/resources/gene_expression.py +++ b/api/resources/gene_expression.py @@ -1,26 +1,12 @@ -""" -Reena Obmina | BCB330 Project 2025-2026 | University of Toronto - -REST endpoint for gene expression queries across all eFP databases. - -Routes: GET /gene_expression/expression// - -All gene IDs are validated by species before reaching the query layer. -Probeset conversion is applied automatically for microarray databases. -""" from flask_restx import Namespace, Resource from markupsafe import escape from api.services.efp_data import query_efp_database_dynamic from api.utils.bar_utils import BARUtils from api.utils.gene_id_utils import ( - CROSS_SPECIES_DATABASES, DATABASE_SPECIES, - PROBESET_DATABASES, - convert_gene_to_probeset, - is_probeset_id, - normalize_gene_id, - validate_gene_id, + GeneIdUtils, + DATABASE_EFP_PROJECT, ) gene_expression = Namespace( @@ -46,38 +32,21 @@ ) class GeneExpression(Resource): def get(self, database, gene_id): - """Retrieve expression values for a gene from a given eFP database. - """ + """Retrieve expression values for a gene from a given eFP database.""" database = str(escape(database)) gene_id = str(escape(gene_id)) - # 1. Resolve database species and expected input species. - # Cross-species databases (e.g. phelipanche) accept an Arabidopsis AGI - # even though the database itself belongs to a different species. species = DATABASE_SPECIES.get(database) if species is None: return BARUtils.error_exit(f"Unknown database '{database}'"), 400 - input_species = CROSS_SPECIES_DATABASES.get(database, species) - # 2. If the caller already supplied a probeset ID, use it directly - if is_probeset_id(gene_id): + if GeneIdUtils.is_probeset_id(gene_id): query_id = gene_id else: - # 3. Validate gene ID format against the expected input species regex - if not validate_gene_id(gene_id, input_species): - return BARUtils.error_exit(f"Invalid {input_species} gene ID: '{gene_id}'"), 400 - - # 4. Normalise (e.g. strip maize transcript suffix _T##) - gene_id = normalize_gene_id(gene_id, species) - - # 5. Microarray / non-direct databases need gene ID -> probeset conversion - if database in PROBESET_DATABASES: - probeset, err = convert_gene_to_probeset(gene_id, species, database) - if err: - return BARUtils.error_exit(err), 404 - query_id = probeset - else: - query_id = gene_id + if not GeneIdUtils.validate_gene_for_database(gene_id, database): + label = DATABASE_EFP_PROJECT.get(database) or species or database + return BARUtils.error_exit(f"Invalid gene ID for {label}: '{gene_id}'"), 400 + query_id = GeneIdUtils.normalize_gene_id(gene_id, species) result = query_efp_database_dynamic(database, query_id) diff --git a/api/utils/bar_utils.py b/api/utils/bar_utils.py index fcf75af..effc28d 100644 --- a/api/utils/bar_utils.py +++ b/api/utils/bar_utils.py @@ -2,6 +2,188 @@ import redis import os +# fmt: off +# Per-eFP-project input validation regexes sourced from efpWeb.cgi. +# Each pattern covers canonical gene IDs AND (where applicable) microarray probeset IDs. +EFP_PROJECT_REGEXES: dict = { + "efp": ( + r"^([Aa][Tt][12345CM][Gg][0-9]{5})$" + r"|^([0-9]{6}(_[xsfi])?_at)$" + r"|^([0-9]{6,9})$" + # ATH1 Affymetrix bacterial/control spike-in probes, shared by all Affy platforms + r"|^(AFFX-(BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX)-(3|5|M)_at)$" + r"|^(AFFX-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre)-(3|5|M)(_|_x_|_s_)at)$" + ), + "efp_arabidopsis": ( + r"^([Aa][Tt][12345CM][Gg][0-9]{5})$" + r"|^([0-9]{6}(_[xsfi])?_at)$" + r"|^([0-9]{6,9})$" + r"|^(AFFX-(BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX)-(3|5|M)_at)$" + r"|^(AFFX-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre)-(3|5|M)(_|_x_|_s_)at)$" + ), + # Seedcoat uses CATMA probes (At\d{8}) and AROS probes (\D\d+_\d+) in addition to ATH1 + "efp_seedcoat": ( + r"^(At[12345CM]g[0-9]{5})$" + r"|^([0-9]{6}(_[xsfi])?_at)$" + r"|^([0-9]{6,9})$" + r"|^(\D\d+_\d+)$" + r"|^(At\d{8})$" + ), + "efp_barley": ( + r"^((HM|HV).*)$|^(HV.*_at)$" + r"|^(([0-9]{4,7})_(Reg|R)_([0-9]{2,4})-([0-9]{4})_at)$" + r"|^([0-9]{4,5}\.AF[0-9]{5}(_|_x_)at)$" + r"|^(A[0-9]{5}\.[0-9]{1}(_|_x_|_s_)at)$" + r"|^(([A-Z]{2}[0-9]{6}|[A-Z]{2}[0-9]{6}\.1)(_|_x_|_s_|_CDS-[0-9]{1,2}_|_CDS-[0-9]{1,2}_s_)at)$" + r"|^(AFFX-(BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX)-(3|5|M)_at)$" + r"|^(AFFX-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre)-(3|5|M)(_|_x_|_s_)at)$" + r"|^(ChlorContig[0-9]{1,2}(_|_x_|_s_)at)$" + r"|^(((MitoContig|Contig)[0-9]{1,6})(_|_x_|_s_)at)$" + r"|^(D[0-9]{5}_at)$" + r"|^(Dhn[0-9]{2}\(Morex\)(_|_s_)at)$" + r"|^(E(Ban|Bca|Bed|Bem|Bes|Bma|Bpi|Bro)[0-9]{2}_SQ[0-9]{3}_[A-Z]{1}[0-9]{2}(_|_s_|_x_)at)$" + r"|^(Franka(_|_b_)3pri[0-9]{1,2}(_|_s_|_x_)at)$" + r"|^(HVSME[a-z]{1}[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f)(_|_x_|_s_)at)$" + r"|^(HV_CEa[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f)(_|_x_|_s_)at)$" + r"|^(H[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{2}[ru](_|_x_|_s_)at)$" + r"|^(S[0-9]{10}[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{1}(_|_x_|_s_)at)$" + r"|^((b|rb)(aak|aal|ags|ah|asd)[0-9]{1,2}[a-z]{1}[0-9]{2}(_|_x_|_s_)at)$" + r"|^(([0-9]{4,7})_(Reg|R)_([0-9]{2,4})-([0-9]{4}))$" + r"|^([0-9]{4,5}\.AF[0-9]{5})$" + r"|^(A[0-9]{5}\.[0-9]{1})$" + r"|^([A-Z]{2}[0-9]{6}|[A-Z]{2}[0-9]{6}\.1)$" + r"|^(AFFX-(BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX))$" + r"|^(AFFX-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre))$" + r"|^(ChlorContig[0-9]{1,2})$" + r"|^((MitoContig|Contig)[0-9]{1,6})$" + r"|^(D[0-9]{5})$" + r"|^(Dhn[0-9]{2}\(Morex\))$" + r"|^(E(Ban|Bca|Bed|Bem|Bes|Bma|Bpi|Bro)[0-9]{2}_SQ[0-9]{3}_[A-Z]{1}[0-9]{2})$" + r"|^(Franka(_|_b_)3pri[0-9]{1,2})$" + r"|^(HVSME[a-z]{1}[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f))$" + r"|^(HV_CEa[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f))$" + r"|^(H[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{2}[ru])$" + r"|^(S[0-9]{10}[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{1})$" + r"|^((b|rb)(aak|aal|ags|ah|asd)[0-9]{1,2}[a-z]{1}[0-9]{2})$" + r"|^(HO)$" + r"|^(MLOC\.[0-9]{4,6}\.[0-9]{1,2})$" + r"|^(AK[0-9]{6}\.1)$" + r"|^(AJ[0-9]{6}\.1)$" + ), + "efp_rice": ( + r"^(LOC_Os[0-9]{2}g[0-9]{5})$" + r"|^((AFFX|AFFX-Os)(-|_)(Ubiquitin|Actin|Cyph|Gapdh|BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX|ef1a|gapdh)(-|_)(3|5|M)_(at|x_at|s_at))$" + r"|^(AFFX-OS-(18SrRNA|25SrRNA|5\.8SrRNA)_(s_at|at))$" + r"|^((AFFX-Mgr-(actin|ef1a|gapdh)-(3|5|M))_(at|x_at|s_at))$" + r"|^(AFFX-r2-Tag(A|B|C|D|E|F|G|H)_at)$" + r"|^(AFFX-r2-Tag(IN|I|J|O|Q)-(3|5|M)_at)$" + r"|^((AFFX|AFFX-Os)-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre)-(3|5|M)(_|_x_|_s_)at)$" + r"|^((Os|OsAffx)\.[0-9]{1,5}\.[0-9]{1}\.(S1|A1|S2)_(at|x_at|s_at|a_at))$" + ), + "efp_medicago": ( + r"^(Medtr\d{1}g\d{6})$" + r"|^(Medtr\d{1}g\d{6}\.[0-9]{1})$" + # Medicago array probesets: Mtr/Msa/Sme prefix, any Affymetrix suffix variant + r"|^(Mtr\.\d{4,5}\.\d+\.(S1|A1|S2)_(at|s_at|x_at|a_at))$" + r"|^(Msa\.\d+\.\d+\.(S1|A1|S2)_(at|s_at|x_at|a_at))$" + r"|^(Sme\.\d+\.\d+\.(S1|A1|S2)_(at|s_at|x_at|a_at))$" + r"|^(AFFX-(Bio|Cre|Dap|Lys|Phe|Thr|Trpn)(B|C|Dn|X)-(3|5|M)_at)$" + r"|^(AFFX-(Msa|Mtr)-(actin|gapc|gsta|ubq11|TrpnX)-(3|5|M)_(at|x_at|s_at))$" + r"|^(AFFX-r2-(Bs|Ec|P1)-(cre|dap|lys|phe|thr|bioB|bioC|bioD)-(3|5|M)_(at|s_at|x_at))$" + r"|^(AFFX-Mtr-ubq11-(3|5|M)_(at|s_at|x_at))$" + r"|^(AFFX-r2-Tag[A-Z]{1,2}_at)$" + r"|^(Medtr_v1_\d{6})$" + ), + "efp_poplar": ( + r"^(Ptp(Affx)?\.\d{1,6}\.\d{1,6}\.(A1|A2|S1|S2)_(x_at|s_at|at|a_at))$" + r"|^((eugene3)\.\d{6,12})$" + r"|^((estExt_)(Genewise|fgenesh)(1|4)\_(v1|kg|pg|pm)(\.|\_v1\.)C_LG_\w{6,10})$" + r"|^((grail3\.)\d{8,12})$" + r"|^((fgenesh)(1|4)\_(kg|pg|pm)\.C\_(scaffold|LG)\_\w{7,12})$" + r"|^((gw1)\.\w{1,6}\.\w{1,4}\.1)$" + r"|^((POPTR)\_[0-9]{4}s[0-9]{5}\.*[1-5]{0,1})$" + # poplar_hormone's real sample IDs omit the transcript suffix entirely + r"|^(Potri\.[0-9]{3}G[0-9]{6}(\.[0-9]{1})?)$" + ), + "efp_soybean": ( + r"^((Glyma\d{1,3}g\d{1,6}\.?\d?)$" + r"|^(Glyma\.\d{1,3}g\d{1,8}))$" + ), + "efp_maize": ( + r"^(AC[0-9]{6}\.[0-9]{1}_FG[0-9]{3})$" + r"|^(AC[0-9]{6}\.[0-9]{1}_FGT[0-9]{3})$" + r"|^(GRMZM(2|5)G[0-9]{6})$" + r"|^(GRMZM(2|5)G[0-9]{6}_T[0-9]{2})$" + r"|^(Zm\d+d\d+)$" + r"|^(Zm\d{1,10}eb\d{1,10})$" + # Maize Affymetrix probeset IDs, e.g. Zm011368_at, Zm039842_s_at + r"|^(Zm\d{6}(_[xsa])?_at)$" + ), + # TaAffx.* probes occur alongside Ta.* — handle both prefixes + "efp_triticale": r"^((Ta|TaAffx)\.\d+\.\d+\.[A-Z]\d+_(at|s_at|x_at|a_at))$", + # Affymetrix human probeset IDs (1557575_at, 202019_s_at) plus a loose fallback + "efp_human": r"^(\d{6,7}(_[xsa])?_at)$|^(\D{0,12}\d{0,12})$|^(\d{1,12})$", + # Remaining eFP projects, sourced verbatim from Vincent's efp_regex_audit_prod.csv + "efp_Eutrema": r"^(Thhalv\d{8}m\.g)$|^(XLOC_\d{6})$|^(nXLOC\d{6})$|^(At\dg\d{5})$", + "efp_actinidia": r"^(Acc\d+\.\d{0,3})$", + "efp_apple": r"^(MfusH1_\d\dg\d{1,8})$", + # CSV pattern is lowercase-only; lipid species names use mixed case (e.g. "TG 54:5; ...") + "efp_arabidopsis_lipid": r"(?i)^[a-z0-9\s:;\/\[\]_\+\-]{1,64}$", + "efp_arachis": r"^(Adur\d+_comp\d+_c\d+_seq\d+)$|^(Gyn_Aipa_c\d+_g\d+_i\d+)$|^(Aipa\d+_comp\d+_c\d+_seq\d+)$|^(Gyn_Adur_c\d+_g\d+_i\d+)$", + "efp_brachypodium": r"^(Bradi\d+g\d+.\d)$|^(Bradi\d+s\d+.\d)$|^(Bradi\d+.g\d+)$", + "efp_brachypodium_metabolites": r"(?i)^[a-z\s\-]{1,60}$", + "efp_brassica_rapa": r"^(Bra.\d+g\d{0,10})$", + "efp_cacao_ccn": r"^(CCN-51_Chr\d{1,3}v\d{1,3}_\d{1,9})$", + "efp_cacao_sca": r"^(SCA-6_Chr\d{1,3}v\d{1,3}_\d{1,9})$", + "efp_cacao_tc": r"^(Tc\d+v2_g\d+)$", + "efp_camelina": r"^(Csa\d{0,5}[gs]\d{0,6}.\d{0,3})$|^(At\d[cgm]\d{0,6})$", + "efp_cannabis": r"(^C\d+$)|(^scaffold\d+$)|(^AGQN\d+$)", + "efp_canola": r"^(Bna\D\d{1,3}g\d{1,8}\D)$|^(Bna\Dnng\d{1,8}\D)$", + "efp_durum_wheat": r"^(TrturSVE\d\D\d{1,3}G\d{1,12})$|^(TrturSVE\d\D\d{1,3}G\d{1,12}_ncBOCREA)$", + "efp_euphorbia": r"^(Ep_chr\d_g\d{1,8})$", + "efp_eutrema": r"^(Thhalv\d{8}m\.g)$|^(XLOC_\d{6})$|^(nXLOC\d{6})$|^(At\dg\d{5})$", + "efp_grape": r"^(VIT_\d{1,2}s\d{4}g\d{5})$|^CHRUN[a-z0-9_]{1,20}$|^CHR\d{1,2}[a-z0-9_]{1,2}$", + "efp_kalanchoe": r"^(Kaladp\d+s\d+)$", + "efp_little_millet": r"^(TRINITY_DN\d+_c\d+_g\d+_i\d+)$", + "efp_lupin": r"^(Luan_Oskar_.{1,12}_\d{1,12})$", + # is_efp_gene_valid matches without re.IGNORECASE, so these freeform-text + # patterns (enzyme/metabolite/category NAMES, not gene IDs) need an explicit + # (?i) -- real sample data is mixed-case ("GAPDH (NAD)", "Citric Acid"). + "efp_maize_enzyme": r"(?i)^[a-z0-9\s\-\(\)]{1,50}$", + "efp_maize_metabolite": r"(?i)^[a-z0-9\s,\.\-\(\)_'\+]{1,60}$", + # Lipid species names (TG_52_1, MGDG_38_6), same freeform style as efp_arabidopsis_lipid + "efp_maize_lipid_map": r"(?i)^[a-z0-9\s:;\/\[\]_\+\-]{1,64}$", + # tomato_trait stores root-architecture trait descriptions, not gene IDs + "efp_tomato_trait": r"^[A-Za-z][A-Za-z0-9\s\.,\-\(\)]{1,100}$", + "efp_maize_transcriptomics": r"^(AC[0-9]{6}\.[0-9]{1}_FG[0-9]{3})$|^(AC[0-9]{6}\.[0-9]{1}_FGT[0-9]{3})$|^(GRMZM(2|5)G[0-9]{6})$|^(GRMZM(2|5)G[0-9]{6}_T[0-9]{2})$|^(Zm\d+d\d+)$|^(Zm\d{1,10}eb\d{1,10})$|^(Zm\d{6}(_[xsa])?_at)$", + "efp_mangosteen": r"^(DN\d{1,10})$", + "efp_marchantia": r"^(Mp.{1,3}g\d{1,7}\.?\d{1,3}?)$", + "efp_oat": r"(^N0\.HOG\d{1,10}$|^\D{1,10}\.*\d{1,10}.{1,10}\d{1,10}$)", + "efp_phelipanche": r"^(OrAeBC\d+_\d+\.\d{1,5})|(At\d[gcm]\d{1,6})$", + "efp_physcomitrella": r"^(Pp)\d+s\d+_\d+V\d\.\d$|^Phypa_\d+$", + "efp_potato": r"^(PGSC0003DMG4\d{8})$", + "efp_rice_metabolite": r"(?i)^[a-z0-9,\s\.\-]{1,40}$", + "efp_rice_transcriptomics": r"^(LOC_Os[0-9]{2}g[0-9]{5})$|^((AFFX|AFFX-Os)(-|_)(Ubiquitin|Actin|Cyph|Gapdh|BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX|ef1a|gapdh)(-|_)(3|5|M)_(at|x_at|s_at))$|^(AFFX-OS-(18SrRNA|25SrRNA|5.8SrRNA)_(s_at|at))$|^((AFFX-Mgr-(actin|ef1a|gapdh)-(3|5|M))_(at|x_at|s_at))$|^(AFFX-r2-Tag(A|B|C|D|E|F|G|H)_at)$|^(AFFX-r2-Tag(IN|I|J|O|Q)-(3|5|M)_at)$|^((AFFX|AFFX-Os)-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre)-(3|5|M)(_|_x_|_s_)at)$|^((Os|OsAffx)\.[0-9]{1,5}\.[0-9]{1}\.(S1|A1|S2)_(at|x_at|s_at|a_at))$", + "efp_selaginella": r"^(Smo\d+)$", + "efp_sorghum": r"^(Sobic.\d{0,5}G\d{0,10}$|^Sobic.K\d{0,10}$|^ENSRNA\d{0,12}$|^SORBI_\d{1,6}G\d{1,10})$", + "efp_strawberry": r"^(FvH4_c?\d{1,3}g\d{1,7})$|^(gene\d{1,10})$", + "efp_striga": r"^(StHeBC3\_\d+\.\d{1,5})$|^(At\d[gcm]\d{1,6})$", + "efp_tomato": r"^(Solyc\d{2}g\d{6}\.?\d{0,3})$|^(TU\d{6})$", + "efp_triphysaria": r"^(TrVeBC\d+_\d+\.\d{1,5})$|^(At\d[gcm]\d{1,6})$", + "efp_tung_tree": r"^(Vf\d+G\d+)$", + "efp_wheat": r"^(TraesCS\d\D\d{0,2}[G]\d{0,6}L*C*\.*\d*)$|^(TraesCSU\d+G\d+L*C*\.*\d*)$", + "efpconfig": r".{0,16}", + "mouse_efp": r"^(XM_\d{0,8}\.\d{0,3})$|^(\d{1,10}\D\d{0,4}\D{0,4})$|^(\D{1,8}\d{0,8}\D{0,8})$|^(ENSMUSG\d{1,15})$|^(NM_\d{0,12}\d.\d{0,3})$", +} +# Aliases for alternate eFP project key spellings used by the BAR +EFP_PROJECT_REGEXES["efpbarley"] = EFP_PROJECT_REGEXES["efp_barley"] +EFP_PROJECT_REGEXES["efprice"] = EFP_PROJECT_REGEXES["efp_rice"] +EFP_PROJECT_REGEXES["efpmedicago"] = EFP_PROJECT_REGEXES["efp_medicago"] +EFP_PROJECT_REGEXES["efppop"] = EFP_PROJECT_REGEXES["efp_poplar"] +EFP_PROJECT_REGEXES["efpsoybean"] = EFP_PROJECT_REGEXES["efp_soybean"] +EFP_PROJECT_REGEXES["maizeefp"] = EFP_PROJECT_REGEXES["efp_maize"] +# fmt: on + class BARUtils: @staticmethod @@ -43,41 +225,138 @@ def normalize_arabidopsis_gene(gene): return "At" + lowered[2:] return gene + @staticmethod + def is_actinidia_gene_valid(gene): + """Validates kiwifruit (Actinidia) gene IDs: Acc23558.1""" + return bool(gene and re.search(r"^Acc\d{5}\.\d+$", gene, re.I)) + + @staticmethod + def is_apple_gene_valid(gene): + """Validates apple gene IDs: MfusH1_01g00343""" + return bool(gene and re.search(r"^MfusH1_\d{2}g\d{5}$", gene, re.I)) + + @staticmethod + def is_barley_gene_valid(gene): + """Validates barley gene IDs: HORVU0Hr1G000320, HORVU.MOREX.r3.1HG0003350.1, + or HORVU.MOREX.r3.UnG0797170.1 (Un = unplaced scaffold, no chromosome digit)""" + return bool( + gene and re.search(r"^HORVU(\d+Hr\d+G\d+|\.MOREX\.r\d+\.(\dH|Un)G\d+\.\d+)$", gene, re.I) + ) + + @staticmethod + def is_brachypodium_gene_valid(gene): + """Validates Brachypodium gene IDs: Bradi1g04930.1""" + return bool(gene and re.search(r"^Bradi\d+g\d+\.\d+$", gene, re.I)) + + @staticmethod + def is_cacao_gene_valid(gene): + """Validates cacao gene IDs: CCN-51_Chr1v1_08396, SCA-6_Chr1v1_00610, Tc01v2_g002690""" + return bool(gene and re.search(r"^((CCN-51|SCA-6)_Chr\d+v\d+_\d+|Tc\d+v\d+_g\d+)$", gene)) + + @staticmethod + def is_camelina_gene_valid(gene): + """Validates Camelina gene IDs: Csa01g012560.1, Csa00462s060.1""" + return bool(gene and re.search(r"^Csa\d+[gs]\d+\.\d+$", gene, re.I)) + + @staticmethod + def is_cassava_gene_valid(gene): + """Validates cassava gene IDs: Manes.01G040000.v8.1""" + return bool(gene and re.search(r"^Manes\.\d{2}G\d+\.v\d+\.\d+$", gene, re.I)) + + @staticmethod + def is_cuscuta_gene_valid(gene): + """Validates Cuscuta gene IDs: Cc000663.t1 or Cc000082""" + return bool(gene and re.search(r"^Cc\d+(\.t\d+)?$", gene, re.I)) + + @staticmethod + def is_eucalyptus_gene_valid(gene): + """Validates Eucalyptus gene IDs: Eucgr.A01716""" + return bool(gene and re.search(r"^Eucgr\.[A-Z]\d+$", gene, re.I)) + + @staticmethod + def is_euphorbia_gene_valid(gene): + """Validates Euphorbia gene IDs: Ep_chr1_g00698""" + return bool(gene and re.search(r"^Ep_chr\d+_g\d+$", gene, re.I)) + @staticmethod def is_grape_gene_valid(gene): - """This function verifies if grape gene is valid: VIT_00s0120g00060 - :param gene: - :return: - """ - if re.search(r"^VIT_\d{0,3}\D\d{0,5}g\d{0,6}$", gene, re.I): - return True - else: - return False + """Validates grape gene IDs: CHR11_JGVV37_114_T01, CHR2_GSVIVT00001265001_T01, + CHRUN_JGVV479_1_T01 (CHRUN = unplaced), or legacy VIT_00s0120g00060""" + return bool( + gene + and re.search( + r"^(CHR(\d+|UN)_[A-Z]+\d+(_\d+)?_T\d+|VIT_\d{0,3}\D\d{0,5}g\d{0,6})$", gene, re.I + ) + ) @staticmethod def is_poplar_gene_valid(gene): - """This function verifies if Poplar v3 gene is valid + """This function verifies if Poplar v3 gene (Potri.001G123456.1) or World Map + atlas probe (Potri.T174200) is valid :param gene: :return: True if valid """ - if re.search(r"^POTRI\.\d{3}g\d{6}.?\d{0,3}$", gene, re.I): + if re.search(r"^POTRI\.(\d{3}G\d{6}\.?\d{0,3}|T\d{6})$", gene, re.I): return True else: return False @staticmethod def is_rice_gene_valid(gene, isoform_id=False): - """This function verifies if rice gene is valid - :param gene: - :param isoform_id: True if you want to verifiy isoform ID - :return: True if valid - """ + """Validates rice gene IDs: LOC_Os01g01430, LOC_Os01g01430.1 (isoform), or Os01g0138100""" + if not gene: + return False if isoform_id and re.search(r"^LOC_Os\d{2}g\d{5}\.\d{1,2}$", gene, re.I): return True - elif isoform_id is False and re.search(r"^LOC_Os\d{2}g\d{5}$", gene, re.I): + if not isoform_id and re.search(r"^LOC_Os\d{2}g\d{5}$", gene, re.I): return True - else: - return False + if re.search(r"^Os\d{2}g\d+$", gene, re.I): + return True + return False + + @staticmethod + def is_spruce_gene_valid(gene): + """Validates spruce clone IDs from either of two cDNA libraries: + GQ0031_G08.1 or WS0321_C07.1 / WS03217_B11.1""" + return bool(gene and re.search(r"^(GQ|WS)\d{4,5}_[A-Z]\d{2}\.\d+$", gene)) + + @staticmethod + def is_sugarcane_gene_valid(gene): + """Validates sugarcane gene IDs: Sh01_g004010 or BAC-clone-based + Sh_209L02_contig-1_g000020 / Sh_135M16_g000010""" + return bool( + gene and re.search(r"^(Sh\d+_g\d+|Sh_[A-Z0-9]+(_contig-\d+)?_g\d+)$", gene, re.I) + ) + + @staticmethod + def is_sunflower_gene_valid(gene): + """Validates sunflower gene IDs: Ha10_00000854""" + return bool(gene and re.search(r"^Ha\d+_\d+$", gene, re.I)) + + @staticmethod + def is_tung_tree_gene_valid(gene): + """Validates tung tree gene IDs: Vf01G0116""" + return bool(gene and re.search(r"^Vf\d+G\d+$", gene, re.I)) + + @staticmethod + def is_wheat_gene_valid(gene): + """Validates wheat gene IDs: TraesCS1A01G268900LC, TraesCS1A02G311600LC.1, TrturSVE1A02G00066260""" + return bool( + gene + and re.search(r"^(TraesCS[0-9A-Z]+(\.\d+)?|TrturSVE[0-9A-Z]+G\d+)$", gene, re.I) + ) + + @staticmethod + def is_willow_gene_valid(gene): + """Validates willow Trinity gene IDs: comp170315_c0_seq1""" + return bool(gene and re.search(r"^comp\d+_c\d+_seq\d+$", gene, re.I)) + + @staticmethod + def is_thellungiella_gene_valid(gene): + """Validates native Thellungiella (Eutrema salsugineum) gene IDs. + Accepts Thhalv format (Thhalv10000089m.g) and novel locus IDs (nXLOC_003010). + """ + return bool(re.search(r"^Thhalv\d+m\.g$", gene) or re.search(r"^nXLOC_\d+$", gene)) @staticmethod def is_tomato_gene_valid(gene, isoform_id=False): @@ -88,7 +367,7 @@ def is_tomato_gene_valid(gene, isoform_id=False): """ if isoform_id and re.search(r"^Solyc\d\dg\d{6}\.\d\.\d$", gene, re.I): return True - elif isoform_id is False and re.search(r"^Solyc\d\dg\d{6}$", gene, re.I): + elif isoform_id is False and re.search(r"^Solyc\d\dg\d{6}(\.\d+)?$", gene, re.I): return True else: return False @@ -106,14 +385,18 @@ def is_cannabis_gene_valid(gene): @staticmethod def is_canola_gene_valid(gene): - """This function verifies if canola gene (BnaC07g42830D) is valid - :param gene: - :return: - """ - if re.search(r"^Bna[AC]\d{2}g\d{5}[A-D]?$", gene, re.I): - return True - else: - return False + """Validates canola gene IDs: BnaA01g34660D, BoC01g03100.09V4, BoBC_1096g00001.01V4, + legacy BrChr4g00368.01V4 / BrBA_1327g00001.01V4 (canola_original* dbs), or + legacy EST contig IDs (Contig18943)""" + return bool( + gene + and re.search( + r"^(Bna[AC]\d{2}g\d{5}[A-D]?|Bo[A-Z]+_?\d+g\d+\.\d+V\d+" + r"|Br(Chr\d{1,2}|BA_\d+)g\d{5}\.\d{2}V\d|Contig\d+)$", + gene, + re.I, + ) + ) @staticmethod def is_arachis_gene_valid(gene): @@ -128,14 +411,77 @@ def is_arachis_gene_valid(gene): @staticmethod def is_brassica_rapa_gene_valid(gene): - """This function verifies if Brassica rapa gene is valid: BraA01g000010 - :param gene: - :return: True if valid - """ - if gene and re.search(r"^BraA.{1,4}g\d{1,9}$", gene, re.I): - return True - else: - return False + """Validates Brassica rapa gene IDs: BraA01g000010 or A01g510040.1_BraROA""" + return bool( + gene + and re.search(r"^(BraA.{1,4}g\d{1,9}|[A-Z]\d{2}[gp]\d+\.\d+_BraROA)$", gene, re.I) + ) + + @staticmethod + def is_human_gene_valid(gene): + """Validates human NCBI Entrez gene IDs (10057), HGNC gene symbols (KRT79, + MIR1285-1), and Ensembl clone-based names (RP11-108K3.3, CTD-2162K18.3, + AC012360.2) used by RNA-seq atlases like human_body_map_2""" + return bool( + gene + and re.search( + r"^\d{1,10}$" + r"|^[A-Z][A-Z0-9]{1,9}(-\d{1,3})?$" + r"|^[A-Z]{2,4}\d{0,3}-\d{2,4}[A-Z]\d{1,3}\.\d{1,3}$" + r"|^A[CL]\d{6}\.\d{1,3}$", + gene, + re.I, + ) + ) + + @staticmethod + def is_little_millet_gene_valid(gene): + """Validates little millet Trinity gene IDs: TRINITY_DN101568_c0_g1_i1""" + return bool(gene and re.search(r"^TRINITY_DN\d+_c\d+_g\d+_i\d+$", gene, re.I)) + + @staticmethod + def is_lupin_gene_valid(gene): + """Validates lupin gene IDs: Luan_Oskar_PB12_103067 or Luan_Oskar_Trin_111463""" + return bool(gene and re.search(r"^Luan_Oskar_(PB\d+|Trin)_\d+$", gene, re.I)) + + @staticmethod + def is_mangosteen_gene_valid(gene): + """Validates mangosteen Trinity gene IDs: DN118788""" + return bool(gene and re.search(r"^DN\d+$", gene, re.I)) + + @staticmethod + def is_marchantia_gene_valid(gene): + """Validates Marchantia polymorpha gene IDs: Mp1g01370.1, or unplaced-scaffold + Mpzg00730.1""" + return bool(gene and re.search(r"^Mp\w{1,3}g\d+\.\d+$", gene, re.I)) + + @staticmethod + def is_medicago_gene_valid(gene): + """Validates Medicago gene IDs: Medtr1g018805, Medtr0010s0370, MtrunA17Chr1g0153991, Medtr_v1_003290""" + return bool( + gene + and re.search(r"^(Medtr(\d+[gs]\d+|_v1_\d+)|MtrunA17Chr\dg\d+)$", gene, re.I) + ) + + @staticmethod + def is_mouse_gene_valid(gene): + """Validates mouse RefSeq transcript IDs: XM_122892.1""" + return bool(gene and re.search(r"^XM_\d+\.\d+$", gene, re.I)) + + @staticmethod + def is_oat_gene_valid(gene): + """Validates oat gene IDs: AVESA.00001b.r1.2AG01080490""" + return bool(gene and re.search(r"^AV[A-Z]{3}\.\d{5}[a-z]\.r\d+\.\d[A-Z]{2}\d{8}$", gene)) + + @staticmethod + def is_potato_gene_valid(gene): + """Validates potato gene IDs: PGSC0003DMG400001801 or EPlSTUG00000003328""" + return bool(gene and re.search(r"^(PGSC0003DMG\d+|EPlSTUG\d+)$", gene, re.I)) + + @staticmethod + def is_quinoa_gene_valid(gene): + """Validates quinoa gene IDs: CquiG00000000055""" + return bool(gene and re.search(r"^CquiG\d+$", gene, re.I)) @staticmethod def is_soybean_gene_valid(gene): @@ -150,29 +496,25 @@ def is_soybean_gene_valid(gene): @staticmethod def is_maize_gene_valid(gene): - """This function verifies if maize gene is valid: Zm00001d046170 - :param gene: - :return: True if valid - """ - if gene and re.search( - r"^(AC[0-9]{6}\.[0-9]{1}_FG[0-9]{3})|(AC[0-9]{6}\.[0-9]{1}_FGT[0-9]{3})|(GRMZM(2|5)G[0-9]{6})|(GRMZM(2|5)G[0-9]{6}_T[0-9]{2})|(Zm\d+d\d+)$", - gene, - re.I, - ): - return True - else: - return False + """Validates maize gene IDs: Zm00001d046170, Zm00001eb006030, AC195946.3_FG003, GRMZM2G000116""" + return bool( + gene + and re.search( + r"^(AC[0-9]{6}\.[0-9]+_FGT?[0-9]{3}|GRMZM[25]G[0-9]{6}(_T[0-9]{2})?|Zm\d+(d|eb)\d+)$", + gene, + re.I, + ) + ) @staticmethod def is_sorghum_gene_valid(gene): - """This function verifies if Arabidopsis gene is valid - :param gene: - :return: - """ - if re.search(r"^(Sobic.\d{0,5}G\d{0,10}|Sobic.K\d{0,10})$", gene, re.I): - return True - else: - return False + """Validates sorghum gene IDs: Sobic.001G003400, Sobic.001G085800.1, SORBI_3001G060800, ENSRNA049471574""" + return bool( + gene + and re.search( + r"^(Sobic\.\d+G\d+(\.\d+)?|Sobic\.K\d+|SORBI_\d+G\d+|ENSRNA\d+)$", gene, re.I + ) + ) @staticmethod def is_kalanchoe_gene_valid(gene): @@ -281,6 +623,23 @@ def format_poplar(poplar_gene): """ return poplar_gene.translate(str.maketrans("pOTRIg", "PotriG")) + @staticmethod + def is_efp_gene_valid(gene: str, efp_project: str) -> bool: + """Validate a gene ID against the named eFP project's input regex. + + Accepts both canonical gene IDs (e.g. AT1G01010 for Arabidopsis) and + microarray probeset IDs (e.g. 267643_at, Contig7905_at) depending on the + project. Returns False if the eFP project name is unknown. + + :param gene: Gene identifier to validate + :param efp_project: eFP project key (e.g. 'efp_arabidopsis', 'efpbarley') + :return: True if the gene ID matches the project's accepted format + """ + pattern = EFP_PROJECT_REGEXES.get(efp_project) + if not pattern: + return False + return bool(re.search(pattern, gene)) + @staticmethod def connect_redis(): """This function connects to redis diff --git a/api/utils/efp_utils.py b/api/utils/efp_utils.py index 533016a..74fb30e 100644 --- a/api/utils/efp_utils.py +++ b/api/utils/efp_utils.py @@ -57,12 +57,12 @@ def is_efp_input_valid(efp, view, mode, gene_1, gene_2=None): # Maybe this part could be improved if efp == "efp_arabidopsis": - # Validate gene ids - if not BARUtils.is_arabidopsis_gene_valid(gene_1): + # Accept AGI format (AT1G01010) or microarray probeset IDs (267643_at) + if not BARUtils.is_efp_gene_valid(gene_1, "efp_arabidopsis"): return False, "Gene 1 is invalid." if mode == "Compare": - if not BARUtils.is_arabidopsis_gene_valid(gene_2): + if not BARUtils.is_efp_gene_valid(gene_2, "efp_arabidopsis"): return False, "Gene 2 is invalid." if efp == "efp_arachis": diff --git a/api/utils/gene_id_utils.py b/api/utils/gene_id_utils.py index e326c92..64ee294 100644 --- a/api/utils/gene_id_utils.py +++ b/api/utils/gene_id_utils.py @@ -1,50 +1,16 @@ -""" -Reena Obmina | BCB330 Project 2025-2026 | University of Toronto - -Gene identifier utilities: species detection, format validation, and probeset conversion. - -Probeset IDs (Affymetrix chips) end in '_at', e.g.: - 261585_at (Arabidopsis ATH1) - AB004882_at (Maize gdowns — GenBank accession probesets) - PtpAffx.224570.1.S1_at (Poplar) - TU000001 (Tomato Rose Lab Atlas — Tomato Unigene chip, no _at suffix) - -Note: not all non-_at IDs are gene IDs. Some databases (e.g. Tomato, Soybean) use gene-model -IDs as their primary key rather than Affymetrix probe IDs. - -Only Arabidopsis AGI-to-probeset conversion is fully implemented. -All other species with pending lookup tables return an actionable error message. -""" - from __future__ import annotations import re -from typing import Optional from api.utils.bar_utils import BARUtils -# --------------------------------------------------------------------------- -# Probeset detection -# --------------------------------------------------------------------------- - -# Most chips: ends in _at (e.g. 261585_at, PtpAffx.200227.1.S1_s_at) -# AROS chip: A######_## format (e.g. A000011_01) _PROBESET_RE = re.compile(r"^.+_at$", re.IGNORECASE) _AROS_PROBESET_RE = re.compile(r"^A\d{6}_\d{2}$", re.IGNORECASE) - - -def is_probeset_id(gene_id: str) -> bool: - """True if gene_id is already a probeset (ends in _at or is AROS format).""" - return bool(_PROBESET_RE.match(gene_id) or _AROS_PROBESET_RE.match(gene_id)) - - -# --------------------------------------------------------------------------- -# Database → species map -# --------------------------------------------------------------------------- +# CATMA microarray probes used by the Seedcoat database (e.g. At30023977) +_CATMA_PROBE_RE = re.compile(r"^At\d{8}$") # fmt: off DATABASE_SPECIES: dict[str, str] = { - # Arabidopsis "affydb": "arabidopsis", "arabidopsis_ecotypes": "arabidopsis", "atgenexp": "arabidopsis", @@ -71,35 +37,29 @@ def is_probeset_id(gene_id: str) -> bool: "root_Schaefer_lab": "arabidopsis", "rpatel": "arabidopsis", "seed_db": "arabidopsis", - "seedcoat": "arabidopsis", # AROS chip; A######_## probesets + "seedcoat": "arabidopsis", "shoot_apex": "arabidopsis", "silique": "arabidopsis", "single_cell": "arabidopsis", - # Actinidia (kiwifruit) "actinidia_bud_development": "actinidia", "actinidia_flower_fruit_development": "actinidia", "actinidia_postharvest": "actinidia", "actinidia_vegetative_growth": "actinidia", - # Apple "apple": "apple", - # Arachis (peanut) "arachis": "arachis", - # Barley "barley_mas": "barley", "barley_rma": "barley", "barley_seed": "barley", "barley_spike_meristem": "barley", "barley_spike_meristem_v3": "barley", - # Brachypodium "brachypodium": "brachypodium", "brachypodium_Bd21": "brachypodium", "brachypodium_embryogenesis": "brachypodium", "brachypodium_grains": "brachypodium", "brachypodium_metabolites_map": "brachypodium", "brachypodium_photo_thermocycle": "brachypodium", - # Brassica rapa "brassica_rapa": "brassica", - # Cacao + "brassica_rapa_developmental_atlas": "brassica", "cacao_developmental_atlas": "cacao", "cacao_developmental_atlas_sca": "cacao", "cacao_drought_diurnal_atlas": "cacao", @@ -108,53 +68,38 @@ def is_probeset_id(gene_id: str) -> bool: "cacao_leaf": "cacao", "cacao_meristem_atlas_sca": "cacao", "cacao_seed_atlas_sca": "cacao", - # Camelina "camelina": "camelina", "camelina_tpm": "camelina", - # Cannabis "cannabis": "cannabis", - # Canola (Brassica napus) "canola": "canola", "canola_original": "canola", "canola_original_v2": "canola", "canola_seed": "canola", - # Cassava "cassava_atlas": "cassava", "cassava_cbb": "cassava", "cassava_eacmv": "cassava", - # Cuscuta "cuscuta": "cuscuta", "cuscuta_early_haustoriogenesis": "cuscuta", "cuscuta_lmd": "cuscuta", - # Wheat / Durum "durum_wheat_abiotic_stress": "wheat", "durum_wheat_biotic_stress": "wheat", "durum_wheat_development": "wheat", - # Eucalyptus "eucalyptus": "eucalyptus", - # Euphorbia "euphorbia": "euphorbia", - # Grape "grape_developmental": "grape", - # Heterodera (nematode) "heterodera_schachtii": "heterodera", - # Human "human_body_map_2": "human", "human_developmental": "human", "human_developmental_SpongeLab": "human", "human_diseased": "human", - # Kalanchoe "kalanchoe": "kalanchoe", "kalanchoe_time_course_analysis": "kalanchoe", - # Little millet "little_millet": "little_millet", - # Lupin "lupin_lcm_leaf": "lupin", "lupin_lcm_pod": "lupin", "lupin_lcm_stem": "lupin", "lupin_pod_seed": "lupin", "lupin_whole_plant": "lupin", - # Maize "maize_RMA_linear": "maize", "maize_RMA_log": "maize", "maize_atlas": "maize", @@ -164,7 +109,7 @@ def is_probeset_id(gene_id: str) -> bool: "maize_ears": "maize", "maize_embryonic_leaf_development": "maize", "maize_enzyme": "maize", - "maize_gdowns": "maize", # Affymetrix chip; GRMZM* → AB*_at (GenBank accession probesets) + "maize_gdowns": "maize", "maize_iplant": "maize", "maize_kernel_v5": "maize", "maize_leaf_gradient": "maize", @@ -174,7 +119,6 @@ def is_probeset_id(gene_id: str) -> bool: "maize_rice_comparison": "maize", "maize_root": "maize", "maize_stress_v5": "maize", - # Mangosteen "mangosteen_aril_vs_rind": "mangosteen", "mangosteen_callus": "mangosteen", "mangosteen_diseased_vs_normal": "mangosteen", @@ -182,43 +126,33 @@ def is_probeset_id(gene_id: str) -> bool: "mangosteen_seed_development": "mangosteen", "mangosteen_seed_development_germination": "mangosteen", "mangosteen_seed_germination": "mangosteen", - # Marchantia "marchantia_organ_stress": "marchantia", - # Medicago - "medicago_mas": "medicago", # Affymetrix chip; Medtr* → Mtr.*_at + "medicago_mas": "medicago", "medicago_rma": "medicago", "medicago_root": "medicago", "medicago_root_v5": "medicago", "medicago_seed": "medicago", - # Mouse "mouse_db": "mouse", - # Oat "oat": "oat", - # Phelipanche "phelipanche": "phelipanche", - # Physcomitrella "physcomitrella_db": "physcomitrella", - # Poplar - "poplar": "poplar", # Affymetrix chip; grail3.* → PtpAffx.*_at + "poplar": "poplar", "poplar_hormone": "poplar", "poplar_leaf": "poplar", "poplar_xylem": "poplar", - # Potato "potato_dev": "potato", "potato_stress": "potato", "potato_wounding": "potato", - # Rice + "quinoa_nutrient": "quinoa", "rice_abiotic_stress_sc_pseudobulk": "rice", "rice_drought_heat_stress": "rice", "rice_leaf_gradient": "rice", "rice_maize_comparison": "rice", - "rice_mas": "rice", # Affymetrix chip; LOC_Os* → Os.*_at + "rice_mas": "rice", "rice_metabolite": "rice", "rice_rma": "rice", "rice_root": "rice", - # Selaginella "selaginella": "selaginella", - # Sorghum "sorghum_atlas_w_BS_cells": "sorghum", "sorghum_comparative_transcriptomics": "sorghum", "sorghum_developmental": "sorghum", @@ -235,26 +169,18 @@ def is_probeset_id(gene_id: str) -> bool: "sorghum_sulfur_stress": "sorghum", "sorghum_temperature_stress": "sorghum", "sorghum_vascularization_and_internode": "sorghum", - # Soybean "soybean": "soybean", "soybean_embryonic_development": "soybean", "soybean_heart_cotyledon_globular": "soybean", "soybean_senescence": "soybean", "soybean_severin": "soybean", - # Spruce "spruce": "spruce", - # Strawberry "strawberry": "strawberry", - # Striga "striga": "striga", - # Sugarcane "sugarcane_culms": "sugarcane", "sugarcane_leaf": "sugarcane", - # Sunflower "sunflower": "sunflower", - # Thellungiella (Eutrema) "thellungiella_db": "thellungiella", - # Tomato "tomato": "tomato", "tomato_ils": "tomato", "tomato_ils2": "tomato", @@ -268,329 +194,180 @@ def is_probeset_id(gene_id: str) -> bool: "tomato_shade_mutants": "tomato", "tomato_shade_timecourse": "tomato", "tomato_trait": "tomato", - # Triphysaria "triphysaria": "triphysaria", - # Triticale - "triticale": "triticale", # Affymetrix chip; EU* → Ta.*_at + "triticale": "triticale", "triticale_mas": "triticale", - # Tung tree "tung_tree": "tung_tree", - # Wheat "wheat": "wheat", "wheat_abiotic_stress": "wheat", "wheat_embryogenesis": "wheat", "wheat_meiosis": "wheat", "wheat_root": "wheat", - # Willow "willow": "willow", - # Test "sample_data": "arabidopsis", } -# fmt: on - -# --------------------------------------------------------------------------- -# Probeset databases -# Databases where the stored key is a probeset ID, not the canonical gene ID. -# A gene → probeset lookup is required before querying these. -# --------------------------------------------------------------------------- - -PROBESET_DATABASES: frozenset[str] = frozenset( - { - # ── Arabidopsis ATH1 GeneChip ──────────────────────────────────────────── - "affydb", - "arabidopsis_ecotypes", - "atgenexp", - "atgenexp_hormone", - "atgenexp_pathogen", - "atgenexp_plus", - "atgenexp_stress", - "guard_cell", - "hnahal", - "lateral_root_initiation", - "light_series", - "meristem_db", - "meristem_db_new", - "root", - "rohan", - "rpatel", - "seed_db", - # ── Other species Affymetrix chips ─────────────────────────────────────── - # Lookup tables for these are pending; supply probeset directly (e.g. Contig3267_at) - "barley_mas", # Affymetrix Barley1 GeneChip (AK364622 → Contig3045_at) - "barley_rma", # Affymetrix Barley1 GeneChip - "human_developmental", # CCR5 → 206991_s_at - "human_developmental_SpongeLab", - "human_diseased", - "maize_gdowns", # Affymetrix Maize GeneChip (GRMZM* → AB*_at, GenBank accession probesets) - "maize_RMA_linear", # contig-based probesets (GRMZM* → AC*_FGT* format) - "maize_RMA_log", # same chip as maize_RMA_linear - "medicago_mas", # Affymetrix Medicago GeneChip (Medtr* → Mtr.*_at) - "medicago_rma", # Affymetrix Medicago GeneChip - "medicago_seed", # old genome model (Medtr8g* → Medtr_v1_*); confirmed from sample data - "poplar", # Affymetrix Poplar GeneChip (Potri.* → grail3.* → PtpAffx.*_at) - "rice_mas", # Affymetrix Rice GeneChip (LOC_Os* → Os.*_at) - "rice_rma", # Affymetrix Rice GeneChip - "tomato", # Affymetrix Tomato GeneChip (Solyc* → TU* probesets); confirmed from sample data - "triticale", # Affymetrix Wheat/Triticale GeneChip (EU* → Ta.*_at) - "triticale_mas", # Affymetrix Wheat/Triticale GeneChip - # ── Non-Affymetrix species with gene ID ≠ stored key ───────────────────── - # Confirmed from eFP browser: input gene ID differs from the stored key. - # Lookup tables pending for all of these. - "grape_developmental", # VIT_00s0120g00060 → CHRUN_JGVV120_4_T01 - "soybean", # Glyma.XxG* (new Wm82.a4) → GlymaXxg*/GlymaXxs* (old format) - "soybean_embryonic_development", - "soybean_heart_cotyledon_globular", - "soybean_senescence", - "soybean_severin", - # ── Cross-species: input is an Arabidopsis AGI, stored as species gene ID ─ - # See CROSS_SPECIES_DATABASES below for the input validation override. - "phelipanche", # AT1G07890 → OrAeBC5_10.1 - "striga", # AT3G11400 → StHeBC3_1.1 - "thellungiella_db", # AT2G21470 → Thhalv10000089m.g - "triphysaria", # AT1G11260 → TrVeBC3_1.1 - # TODO: seedcoat – AROS chip; A######_## probesets; add once format confirmed - # TODO: strawberry – gene10171 → FvH4_1g00010; lookup table needed - # TODO: physcomitrella – Phypa_166136 → Pp1s103_79V6.1; lookup table needed - # TODO: willow – SapurV1A.* → comp*_c*_seq* (Trinity); assembly mapping needed - # TODO: sunflower – HanXRQChr12g* → Ha1_*; genome version mapping needed - # TODO: camelina – Csa01g* (v6) → Csa*s*.* (old assembly); version mapping needed - } -) - -# --------------------------------------------------------------------------- -# Cross-species databases -# These accept an Arabidopsis AGI as input and convert it to a species probeset. -# Used to override input validation (validate against arabidopsis, not native species). -# --------------------------------------------------------------------------- -CROSS_SPECIES_DATABASES: dict[str, str] = { - # database → species of the expected INPUT gene ID - "phelipanche": "arabidopsis", # AT* AGI → OrAeBC5_* probeset - "striga": "arabidopsis", # AT* AGI → StHeBC3_* probeset - "thellungiella_db": "arabidopsis", # AT* AGI → Thhalv* probeset - "triphysaria": "arabidopsis", # AT* AGI → TrVeBC3_* probeset +# Maps databases that store microarray probeset IDs to their eFP project regex key. +# These databases accept both canonical gene IDs (with AGI→probeset lookup for Arabidopsis) +# AND direct probeset ID input. +# fmt: off +DATABASE_EFP_PROJECT: dict[str, str] = { + # Arabidopsis ATH1 microarray databases — support AGI + probeset input + "affydb": "efp_arabidopsis", + "arabidopsis_ecotypes": "efp_arabidopsis", + "atgenexp": "efp_arabidopsis", + "atgenexp_hormone": "efp_arabidopsis", + "atgenexp_pathogen": "efp_arabidopsis", + "atgenexp_plus": "efp_arabidopsis", + "atgenexp_stress": "efp_arabidopsis", + "guard_cell": "efp_arabidopsis", + "hnahal": "efp_arabidopsis", + "lateral_root_initiation": "efp_arabidopsis", + "light_series": "efp_arabidopsis", + "meristem_db": "efp_arabidopsis", + "meristem_db_new": "efp_arabidopsis", + "root": "efp_arabidopsis", + "rohan": "efp_arabidopsis", + "rpatel": "efp_arabidopsis", + "seed_db": "efp_arabidopsis", + # Seedcoat uses CATMA/AROS probes in addition to AGI + "seedcoat": "efp_seedcoat", + # Non-Arabidopsis microarray databases — probeset input only (no AGI conversion) + # barley_seed / barley_spike_meristem(_v3) and poplar_leaf / poplar_xylem were + # previously (incorrectly) mapped here too: their real sample IDs are plain + # gene IDs (HORVU..., Potri...), not probesets, and were 0% passing this + # override. Removed so they fall back to the barley/poplar species validator, + # which already accepts their format. + "barley_mas": "efp_barley", + "barley_rma": "efp_barley", + "rice_mas": "efp_rice", + "rice_rma": "efp_rice", + "medicago_mas": "efp_medicago", + "medicago_rma": "efp_medicago", + "poplar": "efp_poplar", + "poplar_hormone": "efp_poplar", + "triticale": "efp_triticale", + "triticale_mas": "efp_triticale", + "human_developmental": "efp_human", + "human_developmental_SpongeLab": "efp_human", + "human_diseased": "efp_human", + "maize_gdowns": "efp_maize", + # Added after Task 2 (Jun 2026) regex-coverage audit: species validator rejected + # real sample IDs that Vincent's per-project eFP regex correctly accepts. + "arachis": "efp_arachis", + "canola_seed": "efp_canola", + "thellungiella_db": "efp_eutrema", + "physcomitrella_db": "efp_physcomitrella", + "tomato": "efp_tomato", + "tomato_renormalized": "efp_tomato", + "lipid_map": "efp_arabidopsis_lipid", + # Metabolite/enzyme-class eFPs: real "gene_id" values are compound/enzyme/trait + # names looked up against one fixed database, not actual gene IDs -- see + # scrape_view_databases.py's _HARDCODED comment for how these sites are scraped. + "maize_enzyme": "efp_maize_enzyme", + "maize_metabolite": "efp_maize_metabolite", + "maize_lipid_map": "efp_maize_lipid_map", + "rice_metabolite": "efp_rice_metabolite", + "brachypodium_metabolites_map": "efp_brachypodium_metabolites", + "tomato_trait": "efp_tomato_trait", } +# fmt: on -# --------------------------------------------------------------------------- -# Species detection -# --------------------------------------------------------------------------- - - -def detect_gene_species(gene_id: str) -> Optional[str]: - """Infer species from gene_id format. Returns canonical species key or None.""" - upper = gene_id.upper() - if BARUtils.is_arabidopsis_gene_valid(upper): - return "arabidopsis" - if BARUtils.is_maize_gene_valid(upper): - return "maize" - if BARUtils.is_rice_gene_valid(upper): - return "rice" - if BARUtils.is_soybean_gene_valid(upper): - return "soybean" - if BARUtils.is_poplar_gene_valid(upper): - return "poplar" - if BARUtils.is_tomato_gene_valid(upper): - return "tomato" - if BARUtils.is_sorghum_gene_valid(upper): - return "sorghum" - if BARUtils.is_cannabis_gene_valid(upper): - return "cannabis" - if BARUtils.is_grape_gene_valid(upper): - return "grape" - if BARUtils.is_kalanchoe_gene_valid(upper): - return "kalanchoe" - if BARUtils.is_strawberry_gene_valid(upper): - return "strawberry" - if BARUtils.is_selaginella_gene_valid(upper): - return "selaginella" - if BARUtils.is_phelipanche_gene_valid(upper): - return "phelipanche" - if BARUtils.is_physcomitrella_gene_valid(upper): - return "physcomitrella" - if BARUtils.is_striga_gene_valid(upper): - return "striga" - if BARUtils.is_triphysaria_gene_valid(upper): - return "triphysaria" - if BARUtils.is_canola_gene_valid(upper): - return "canola" - if BARUtils.is_brassica_rapa_gene_valid(upper): - return "brassica" - if BARUtils.is_arachis_gene_valid(upper): - return "arachis" - return None - - -# --------------------------------------------------------------------------- -# Gene ID validation -# --------------------------------------------------------------------------- - -# Species without a validator entry pass through (unknown format = not rejected). -# Note: strawberry and physcomitrella validators match the probeset format -# (FvH4_*, Pp1s*V6.*), not the user-input gene format (gene####, Phypa_*). -# Lookup tables for those are still pending. _VALIDATORS: dict = { - "arabidopsis": BARUtils.is_arabidopsis_gene_valid, - "arachis": BARUtils.is_arachis_gene_valid, - "brassica": BARUtils.is_brassica_rapa_gene_valid, - "cannabis": BARUtils.is_cannabis_gene_valid, - "canola": BARUtils.is_canola_gene_valid, - "grape": BARUtils.is_grape_gene_valid, - "kalanchoe": BARUtils.is_kalanchoe_gene_valid, - "maize": BARUtils.is_maize_gene_valid, - "phelipanche": BARUtils.is_phelipanche_gene_valid, + "actinidia": BARUtils.is_actinidia_gene_valid, + "apple": BARUtils.is_apple_gene_valid, + "arabidopsis": BARUtils.is_arabidopsis_gene_valid, + "arachis": BARUtils.is_arachis_gene_valid, + "barley": BARUtils.is_barley_gene_valid, + "brachypodium": BARUtils.is_brachypodium_gene_valid, + "brassica": BARUtils.is_brassica_rapa_gene_valid, + "cacao": BARUtils.is_cacao_gene_valid, + "camelina": BARUtils.is_camelina_gene_valid, + "cannabis": BARUtils.is_cannabis_gene_valid, + "canola": BARUtils.is_canola_gene_valid, + "cassava": BARUtils.is_cassava_gene_valid, + "cuscuta": BARUtils.is_cuscuta_gene_valid, + "eucalyptus": BARUtils.is_eucalyptus_gene_valid, + "euphorbia": BARUtils.is_euphorbia_gene_valid, + "grape": BARUtils.is_grape_gene_valid, + "heterodera": BARUtils.is_arabidopsis_gene_valid, + "human": BARUtils.is_human_gene_valid, + "kalanchoe": BARUtils.is_kalanchoe_gene_valid, + "little_millet": BARUtils.is_little_millet_gene_valid, + "lupin": BARUtils.is_lupin_gene_valid, + "maize": BARUtils.is_maize_gene_valid, + "mangosteen": BARUtils.is_mangosteen_gene_valid, + "marchantia": BARUtils.is_marchantia_gene_valid, + "medicago": BARUtils.is_medicago_gene_valid, + "mouse": BARUtils.is_mouse_gene_valid, + "oat": BARUtils.is_oat_gene_valid, + "phelipanche": BARUtils.is_phelipanche_gene_valid, "physcomitrella": BARUtils.is_physcomitrella_gene_valid, - "poplar": BARUtils.is_poplar_gene_valid, - "rice": BARUtils.is_rice_gene_valid, - "selaginella": BARUtils.is_selaginella_gene_valid, - "sorghum": BARUtils.is_sorghum_gene_valid, - "soybean": BARUtils.is_soybean_gene_valid, - "strawberry": BARUtils.is_strawberry_gene_valid, - "striga": BARUtils.is_striga_gene_valid, - "tomato": BARUtils.is_tomato_gene_valid, - "triphysaria": BARUtils.is_triphysaria_gene_valid, + "poplar": BARUtils.is_poplar_gene_valid, + "potato": BARUtils.is_potato_gene_valid, + "quinoa": BARUtils.is_quinoa_gene_valid, + "rice": BARUtils.is_rice_gene_valid, + "selaginella": BARUtils.is_selaginella_gene_valid, + "sorghum": BARUtils.is_sorghum_gene_valid, + "soybean": BARUtils.is_soybean_gene_valid, + "spruce": BARUtils.is_spruce_gene_valid, + "strawberry": BARUtils.is_strawberry_gene_valid, + "striga": BARUtils.is_striga_gene_valid, + "sugarcane": BARUtils.is_sugarcane_gene_valid, + "sunflower": BARUtils.is_sunflower_gene_valid, + "thellungiella": BARUtils.is_thellungiella_gene_valid, + "tomato": BARUtils.is_tomato_gene_valid, + "triphysaria": BARUtils.is_triphysaria_gene_valid, + "tung_tree": BARUtils.is_tung_tree_gene_valid, + "wheat": BARUtils.is_wheat_gene_valid, + "willow": BARUtils.is_willow_gene_valid, } - -def validate_gene_id(gene_id: str, species: str) -> bool: - """True if gene_id passes the species validator, or species has no validator.""" - validator = _VALIDATORS.get(species) - return validator(gene_id) if validator is not None else True - - -def get_species_for_database(database: str) -> Optional[str]: - """Return canonical species key for database, or None if unknown.""" - return DATABASE_SPECIES.get(database) - - -# --------------------------------------------------------------------------- -# Gene ID normalisation -# --------------------------------------------------------------------------- - -# Maize transcript IDs (e.g. GRMZM2G083841_T01) must be stripped to gene level -# before querying eFP databases. -_MAIZE_TRANSCRIPT_RE = re.compile(r"_T\d{1,3}$", re.IGNORECASE) - -# Barley V3 IDs from ePlant use a .V3 suffix (e.g. HORVU.MOREX.r3.1HG0000030.V3) -# but databases store a .1 suffix (e.g. HORVU.MOREX.r3.1HG0000030.1). -# Strip any trailing version suffix (.[Vv]\d+ or .\d+) and reattach .1. _BARLEY_V3_RE = re.compile(r"\.[Vv]\d+$") -def normalize_gene_id(gene_id: str, species: str) -> str: - """Return the gene ID in the form stored in eFP databases. - - :param gene_id: Raw gene identifier supplied by the user. - :type gene_id: str - :param species: Canonical species key (e.g. ``'maize'``, ``'barley'``). - :type species: str - :returns: Normalised gene ID ready for database lookup. - :rtype: str - - Maize: strips ``_T##`` transcript suffix (``GRMZM2G083841_T01`` → ``GRMZM2G083841``). - - Barley V3: replaces ``.V3`` version suffix with ``.1`` to match the stored format - (``HORVU.MOREX.r3.1HG0000030.V3`` → ``HORVU.MOREX.r3.1HG0000030.1``). - """ - if species == "maize": - return _MAIZE_TRANSCRIPT_RE.sub("", gene_id) - if species == "barley" and _BARLEY_V3_RE.search(gene_id): - return _BARLEY_V3_RE.sub(".1", gene_id) - return gene_id - - -# --------------------------------------------------------------------------- -# Gene ID → probeset conversion -# --------------------------------------------------------------------------- - - -def convert_gene_to_probeset( - gene_id: str, - species: str, - database: str, -) -> tuple[Optional[str], Optional[str]]: - """Convert gene_id to its probeset ID. Returns (probeset, None) or (None, error).""" - - # ── Implemented ────────────────────────────────────────────────────────── - - if species == "arabidopsis": - from api.services.efp_data import EFPDataService # noqa: PLC0415 - probeset = EFPDataService.agi_to_probset(gene_id.upper()) - if probeset: - return probeset, None - return None, f"No ATH1 probeset found for '{gene_id}'." - - # ── Affymetrix chips (lookup tables pending) ────────────────────────────── - - if species == "barley": - # TODO: AK364622 → Contig3045_at - pass - - if species == "maize": - # TODO: maize_gdowns — GRMZM* → AB*_at (GenBank accession probesets; confirmed from sample data) - # TODO: maize_RMA_linear — GRMZM* → AC*_FGT* (contig-based probesets; confirmed from sample data) - # Other maize databases (maize_buell_lab etc.) store Zm00001d* directly — use normalize_gene_id. - pass - - if species == "medicago": - # TODO: medicago_mas / medicago_rma — Medtr* → Mtr.*_at (Affymetrix chip) - # TODO: medicago_seed — Medtr8g* → Medtr_v1_* (old genome model; confirmed from sample data) - pass - - if species == "poplar": - # TODO: grail3.* → PtpAffx.*_at - pass - - if species == "rice": - # TODO: LOC_Os* → Os.*_at - pass - - if species == "triticale": - # TODO: EU* → Ta.*_at - pass - - if species == "human": - # TODO: gene symbol → numeric_s_at (e.g. CCR5 → 206991_s_at) - pass - - # ── Non-Affymetrix species with differing ID formats (lookup tables pending) ── - - if species == "tomato" and database == "tomato": - # TODO: Solyc* → TU* (Tomato Unigene probesets on Affymetrix Tomato GeneChip) - # Confirmed from sample data: tomato (Rose Lab Atlas) stores TU000001 format. - # tomato_ils / tomato_ils2 store Solyc* directly — no conversion needed for those. - pass - - if species == "grape": - # TODO: VIT_* → CHRUN_* - pass - - if species == "soybean": - # TODO: Glyma.XxG* (new Wm82.a4 format) → GlymaXxg*/GlymaXxs* (old format) - # Confirmed from sample data: soybean/soybean_severin store old format (e.g. Glyma0021s00410). - # This is a gene model version reconciliation, not just string formatting. - pass - - # ── Cross-species: Arabidopsis AGI input → species probeset (lookup tables pending) ── - - if species == "phelipanche": - # TODO: AT* → OrAeBC5_* - pass - - if species == "striga": - # TODO: AT* → StHeBC3_* - pass - - if species == "thellungiella": - # TODO: AT* → Thhalv* - pass - - if species == "triphysaria": - # TODO: AT* → TrVeBC3_* - pass - - return None, ( - f"Probeset lookup not yet available for species '{species}' " - f"(database: '{database}'). " - "Supply the probeset ID directly (e.g. Contig3267_at)." - ) +class GeneIdUtils: + @staticmethod + def is_probeset_id(gene_id: str) -> bool: + """Return True if the gene_id looks like a microarray probeset rather than a gene ID. + + Covers: + - Standard Affymetrix probes ending in _at (e.g. 267643_at, Contig7905_at) + - AROS array probes (e.g. A017813_01) + - CATMA array probes used by the Seedcoat database (e.g. At30023977) + """ + return bool( + _PROBESET_RE.match(gene_id) + or _AROS_PROBESET_RE.match(gene_id) + or _CATMA_PROBE_RE.match(gene_id) + ) + + @staticmethod + def validate_gene_id(gene_id: str, species: str) -> bool: + validator = _VALIDATORS.get(species) + return validator(gene_id) if validator is not None else True + + @staticmethod + def validate_gene_for_database(gene_id: str, database: str) -> bool: + """Validate a gene ID against the rules for a specific database. + + For microarray databases, uses the eFP project regex which accepts both + canonical gene IDs and probeset IDs. Falls back to species-based validation + for all other databases. + + :param gene_id: Gene identifier to validate + :param database: Database name (e.g. 'light_series', 'barley_mas') + :return: True if the gene ID is valid for the given database + """ + efp_project = DATABASE_EFP_PROJECT.get(database) + if efp_project: + return BARUtils.is_efp_gene_valid(gene_id, efp_project) + species = DATABASE_SPECIES.get(database) + return GeneIdUtils.validate_gene_id(gene_id, species) if species else True + + @staticmethod + def normalize_gene_id(gene_id: str, species: str) -> str: + if species == "barley" and _BARLEY_V3_RE.search(gene_id): + return _BARLEY_V3_RE.sub(".1", gene_id) + return gene_id diff --git a/build_master_db_list.py b/build_master_db_list.py new file mode 100644 index 0000000..b77b8c7 --- /dev/null +++ b/build_master_db_list.py @@ -0,0 +1,127 @@ +""" +Reena Obmina | BCB330 Project 2025-2026 | University of Toronto + +Task 4 (Jun 2026): assemble the final "master list" of every BAR database +discovered across both frontends, organized the way Vincent asked for -- +by species, noting eFP vs ePlant vs both, and microarray vs RNA-seq. + +Platform (microarray vs RNA-seq) is determined from the real sample IDs +themselves (GeneIdUtils.is_probeset_id), not from which validator code path +happens to handle a database, since a handful of gene-ID (RNA-seq) databases +are routed through Vincent's per-project eFP regex anyway for better coverage +(see DATABASE_EFP_PROJECT comments in gene_id_utils.py) -- that routing is an +implementation detail, not the underlying data type. + +Note on atgenexp-style databases: a handful of databases (atgenexp_plus, +atgenexp_pathogen, maize_RMA_linear, tomato_renormalized, etc.) bundle multiple +papers/projects into one physical database -- one view per paper, not one view +per database like everywhere else. proj_id_view_mapping.json (built by +build_proj_id_view_mapping.py) already works out, per view, which proj_id(s) +in the real sample data that view actually corresponds to, and classifies the +database as "multi_project" (genuinely separate papers, disjoint proj_ids) vs +"duplicate_view_names" (same proj_id, just different eFP/ePlant display names) +vs "partial_overlap". This script folds that breakdown into the master list +under "proj_id_breakdown" so the per-paper granularity isn't lost when an API +caller only has the database name to go on. + +Reads: data/efp_info/db_source_summary.json -- db -> efp/eplant/both (scrape_species_view_info.py) + db_regex_coverage_report.csv -- per-db validation results (validate_db_regex_coverage.py) + species_databases.json -- project -> view -> db (scrape_view_databases.py) + proj_id_view_mapping.json -- per-view proj_id breakdown (build_proj_id_view_mapping.py) + api/utils/gene_id_utils.DATABASE_SPECIES -- db -> canonical species key +Writes: data/efp_info/master_db_list.json -- { species: { db: {source, platform, views, validation, proj_id_breakdown} } } +""" + +import csv +import json +import sys +import types +from collections import defaultdict +from pathlib import Path + +sys.modules.setdefault("api", types.ModuleType("api")) +sys.modules["api"].__path__ = ["api"] +sys.modules.setdefault("api.utils", types.ModuleType("api.utils")) +sys.modules["api.utils"].__path__ = ["api/utils"] + +from api.utils.gene_id_utils import DATABASE_SPECIES # noqa: E402 + + +def load_coverage(): + with open("db_regex_coverage_report.csv") as f: + return {r["database"]: r for r in csv.DictReader(f)} + + +def load_views_by_db(): + """Invert species_databases.json (project -> view -> db) into db -> {project: [views]}.""" + species_db = json.load(open("species_databases.json")) + views_by_db = defaultdict(lambda: defaultdict(list)) + for project, views in species_db.items(): + for view_name, db in views.items(): + views_by_db[db][project].append(view_name) + return views_by_db + + +def main(): + db_sources = json.load(open("data/efp_info/db_source_summary.json")) + coverage = load_coverage() + views_by_db = load_views_by_db() + proj_id_mapping = json.load(open("proj_id_view_mapping.json")) + + # coverage (db_regex_coverage_report.csv) is the full universe -- every db with + # real sample data in api/random_rows_json/, including ones no longer reachable + # from any live dropdown ("legacy_not_in_dropdown"). db_sources only has the + # live-discoverable subset. Union them so the master list is genuinely complete. + all_dbs = set(coverage) | set(db_sources) + + master = defaultdict(dict) + n_multi_project_dbs = 0 + n_legacy = 0 + for db in sorted(all_dbs): + species = DATABASE_SPECIES.get(db, "unknown") + row = coverage.get(db, {}) + source = row.get("source", db_sources.get(db, "unknown")) + if source == "legacy_not_in_dropdown": + n_legacy += 1 + looks_like_probeset = row.get("looks_like_probeset") == "True" + + entry = { + "source": source, + "platform": "microarray" if looks_like_probeset else "rna_seq", + "views": dict(views_by_db.get(db, {})), + "validation": { + "n_samples": int(row.get("n_samples", 0)), + "n_pass": int(row.get("n_pass", 0)), + "n_fail": int(row.get("n_fail", 0)), + }, + } + + proj_id_info = proj_id_mapping.get(db) + if proj_id_info: + entry["proj_id_breakdown"] = proj_id_info + if proj_id_info["classification"] == "multi_project": + n_multi_project_dbs += 1 + + master[species][db] = entry + + out_file = Path("data/efp_info/master_db_list.json") + with open(out_file, "w") as f: + json.dump(dict(sorted(master.items())), f, indent=2, sort_keys=False) + + n_species = len(master) + n_dbs = sum(len(dbs) for dbs in master.values()) + n_microarray = sum(1 for dbs in master.values() for d in dbs.values() if d["platform"] == "microarray") + n_rna_seq = n_dbs - n_microarray + n_efp_only = sum(1 for dbs in master.values() for d in dbs.values() if d["source"] == "efp") + n_eplant_only = sum(1 for dbs in master.values() for d in dbs.values() if d["source"] == "eplant") + n_both = sum(1 for dbs in master.values() for d in dbs.values() if d["source"] == "both") + + print(f"Species: {n_species} | Databases: {n_dbs} ({n_legacy} legacy/not in any current dropdown)") + print(f" eFP-only: {n_efp_only} | ePlant-only: {n_eplant_only} | both: {n_both}") + print(f" microarray: {n_microarray} | rna_seq: {n_rna_seq}") + print(f" Multi-project databases (e.g. atgenexp_*): {n_multi_project_dbs}") + print(f"Output written to {out_file}") + + +if __name__ == "__main__": + main() diff --git a/build_proj_id_view_mapping.py b/build_proj_id_view_mapping.py new file mode 100644 index 0000000..7a27fe7 --- /dev/null +++ b/build_proj_id_view_mapping.py @@ -0,0 +1,125 @@ +""" +Reena Obmina | BCB330 Project 2025-2026 | University of Toronto + +Task 3 (Jun 11 2026): for databases like atgenexp where multiple eFP/ePlant +views/papers share one physical database, derive which proj_id(s) belong to +which view, by cross-referencing each view's known sample names (from Task 1's +XML scrape) against the real proj_id values recorded for those exact sample +names in the production sample data. + +A database is "genuinely multi-project" if its views resolve to disjoint (or +mostly disjoint) proj_id sets — i.e. each view really is a separate +paper/experiment. If two differently-named views resolve to the same proj_id +set, they're not separate projects — just the eFP and ePlant frontends using +different display names for the one underlying dataset. + +Reads: data/efp_info/efp_eplant_species_view_info.json — view -> sample names (Task 1) + api/random_rows_json/{db}_test_data.json — real (proj_id, data_bot_id) pairs +Writes: proj_id_view_mapping.json — per multi-view db: view -> proj_id set, + classified as "multi_project" or "duplicate_view_names" +""" + +import json +from collections import defaultdict +from pathlib import Path + +INFO_PATH = "data/efp_info/efp_eplant_species_view_info.json" +SAMPLE_DIR = Path("api/random_rows_json") + + +def build_view_samples(): + """Map (db, view_name) -> set of sample names, from Task 1's XML scrape.""" + info = json.load(open(INFO_PATH)) + view_samples = defaultdict(set) + for source in ("efp", "eplant"): + for _key, views in info[source].items(): + for v in views: + db = v.get("database") + if not db: + continue + samples = set() + for group in v.get("groups", {}).values(): + samples.update(group.get("controls", [])) + for tissue_samples in group.get("treatments", {}).values(): + samples.update(tissue_samples) + view_samples[(db, v["view_name"])] |= samples + return view_samples + + +def load_bot_to_proj(db): + path = SAMPLE_DIR / f"{db}_test_data.json" + if not path.exists(): + return {} + rows = json.load(open(path)) + bot_to_proj = defaultdict(set) + for row in rows: + bot_id = row.get("data_bot_id") + proj_id = row.get("proj_id") + if bot_id is not None and proj_id is not None: + bot_to_proj[bot_id].add(str(proj_id)) + return bot_to_proj + + +def main(): + view_samples = build_view_samples() + + by_db = defaultdict(dict) + for (db, view_name), samples in view_samples.items(): + by_db[db][view_name] = samples + + multi_view_dbs = {db: views for db, views in by_db.items() if len(views) > 1} + + report = {} + for db, views in sorted(multi_view_dbs.items()): + bot_to_proj = load_bot_to_proj(db) + view_proj_ids = {} + for view_name, samples in views.items(): + proj_ids = set() + matched = 0 + for s in samples: + if s in bot_to_proj: + proj_ids |= bot_to_proj[s] + matched += 1 + view_proj_ids[view_name] = { + "n_view_samples": len(samples), + "n_matched_in_real_data_sample": matched, + "proj_ids": sorted(proj_ids), + } + + # Classify: do any two views share NO proj_ids in common (genuine + # separate projects) vs all views resolving to the same proj_id set + # (same project, just different eFP/ePlant display names)? + proj_id_sets = [set(v["proj_ids"]) for v in view_proj_ids.values() if v["proj_ids"]] + if len(proj_id_sets) < 2: + classification = "insufficient_data" + else: + all_identical = all(s == proj_id_sets[0] for s in proj_id_sets) + any_disjoint = any( + proj_id_sets[i].isdisjoint(proj_id_sets[j]) + for i in range(len(proj_id_sets)) + for j in range(i + 1, len(proj_id_sets)) + ) + if all_identical: + classification = "duplicate_view_names" + elif any_disjoint: + classification = "multi_project" + else: + classification = "partial_overlap" + + report[db] = {"classification": classification, "views": view_proj_ids} + + out_file = "proj_id_view_mapping.json" + with open(out_file, "w") as f: + json.dump(report, f, indent=2) + + counts = defaultdict(int) + for r in report.values(): + counts[r["classification"]] += 1 + print(f"Checked {len(report)} multi-view databases.") + for cls, n in sorted(counts.items()): + print(f" {cls}: {n}") + print(f"Report written to {out_file}") + + +if __name__ == "__main__": + main() diff --git a/config/databases/soybean_nssnp.sql b/config/databases/soybean_nssnp.sql index be5b88e..5d5e991 100644 --- a/config/databases/soybean_nssnp.sql +++ b/config/databases/soybean_nssnp.sql @@ -60,8 +60,7 @@ CREATE TABLE `sample_lookup` ( `sample_id` varchar(45) NOT NULL, `dataset` varchar(45) DEFAULT NULL, `dataset_sample` varchar(45) DEFAULT NULL, - PRIMARY KEY (`sample_id`), - CONSTRAINT `sample_id` FOREIGN KEY (`sample_id`) REFERENCES `snps_reference` (`sample_id`) + PRIMARY KEY (`sample_id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; /*!40101 SET character_set_client = @saved_cs_client */; diff --git a/config/databases/tomato_nssnp.sql b/config/databases/tomato_nssnp.sql index 60df4a6..7f75a07 100644 --- a/config/databases/tomato_nssnp.sql +++ b/config/databases/tomato_nssnp.sql @@ -34,8 +34,7 @@ CREATE TABLE `lines_lookup` ( `lines_id` varchar(45) NOT NULL, `species` varchar(35) DEFAULT NULL, `alias` varchar(35) DEFAULT NULL, - PRIMARY KEY (`lines_id`), - CONSTRAINT `lines_id` FOREIGN KEY (`lines_id`) REFERENCES `snps_reference` (`sample_id`) + PRIMARY KEY (`lines_id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb3; /*!40101 SET character_set_client = @saved_cs_client */; diff --git a/config/init.sh b/config/init.sh index c3e4a06..62acb7d 100755 --- a/config/init.sh +++ b/config/init.sh @@ -1,10 +1,11 @@ #!/bin/sh # This script initialized the GitHub environment -# To use locally, set up DB Password below -# The password below is for GitHub Actions. Please do not change. -DB_USER="root" -DB_PASS="root" +# To use locally, set DB_USER/DB_PASS/DB_HOST as environment variables. +# Defaults below are for GitHub Actions — do not change the defaults. +DB_USER=${DB_USER:-"root"} +DB_PASS=${DB_PASS:-"root"} +DB_HOST=${DB_HOST:-"localhost"} # Load the data echo "Welcome to the BAR API. Running init!" @@ -18,36 +19,59 @@ if [ $? -ne 0 ]; then fi echo "Successfully bootstrapped simple eFP databases" -mysql -u $DB_USER -p$DB_PASS < ./config/databases/annotations_lookup.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/arabidopsis_ecotypes.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/arachis.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/canola_nssnp.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/eplant2.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/eplant_poplar.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/eplant_rice.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/eplant_soybean.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/eplant_tomato.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/fastpheno.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/germination.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/homologs_db.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/interactions_vincent_v2.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/kalanchoe.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/klepikova.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/llama3.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/phelipanche.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/physcomitrella_db.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/poplar_nssnp.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/rice_interactions.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/selaginella.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/shoot_apex.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/silique.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/single_cell.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/soybean_nssnp.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/strawberry.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/striga.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/tomato_nssnp.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/tomato_sequence.sql -mysql -u $DB_USER -p$DB_PASS < ./config/databases/triphysaria.sql +db_exists() { + mysql -h $DB_HOST -u $DB_USER -p$DB_PASS -e "SELECT SCHEMA_NAME FROM information_schema.SCHEMATA WHERE SCHEMA_NAME='$1';" 2>/dev/null | grep -q "$1" +} + +import_if_missing() { + DB_NAME=$1 + SQL_FILE=$2 + if db_exists "$DB_NAME"; then + echo "[skip] $DB_NAME already exists" + else + echo "[load] importing $DB_NAME..." + mysql -h $DB_HOST -u $DB_USER -p$DB_PASS < "$SQL_FILE" + fi +} + +import_if_missing annotations_lookup ./config/databases/annotations_lookup.sql +import_if_missing arabidopsis_ecotypes ./config/databases/arabidopsis_ecotypes.sql +import_if_missing arachis ./config/databases/arachis.sql +import_if_missing canola_nssnp ./config/databases/canola_nssnp.sql +import_if_missing eplant2 ./config/databases/eplant2.sql +import_if_missing eplant_poplar ./config/databases/eplant_poplar.sql +import_if_missing eplant_rice ./config/databases/eplant_rice.sql +import_if_missing eplant_soybean ./config/databases/eplant_soybean.sql +import_if_missing eplant_tomato ./config/databases/eplant_tomato.sql +import_if_missing fastpheno ./config/databases/fastpheno.sql +import_if_missing germination ./config/databases/germination.sql +import_if_missing homologs_db ./config/databases/homologs_db.sql +import_if_missing interactions_vincent_v2 ./config/databases/interactions_vincent_v2.sql +import_if_missing kalanchoe ./config/databases/kalanchoe.sql +import_if_missing klepikova ./config/databases/klepikova.sql +import_if_missing llama3 ./config/databases/llama3.sql +import_if_missing phelipanche ./config/databases/phelipanche.sql +import_if_missing physcomitrella_db ./config/databases/physcomitrella_db.sql +import_if_missing poplar_nssnp ./config/databases/poplar_nssnp.sql +import_if_missing rice_interactions ./config/databases/rice_interactions.sql +import_if_missing selaginella ./config/databases/selaginella.sql +import_if_missing shoot_apex ./config/databases/shoot_apex.sql +import_if_missing silique ./config/databases/silique.sql +import_if_missing single_cell ./config/databases/single_cell.sql +import_if_missing soybean_nssnp ./config/databases/soybean_nssnp.sql +import_if_missing strawberry ./config/databases/strawberry.sql +import_if_missing striga ./config/databases/striga.sql +import_if_missing tomato_nssnp ./config/databases/tomato_nssnp.sql +import_if_missing tomato_sequence ./config/databases/tomato_sequence.sql +import_if_missing triphysaria ./config/databases/triphysaria.sql +import_if_missing light_series ./config/databases/light_series.sql +import_if_missing maize_RMA_linear ./config/databases/maize_RMA_linear.sql +import_if_missing meristem_db ./config/databases/meristem_db.sql +import_if_missing potato_stress ./config/databases/potato_stress.sql +import_if_missing seedcoat ./config/databases/seedcoat.sql +import_if_missing soybean ./config/databases/soybean.sql +import_if_missing soybean_severin ./config/databases/soybean_severin.sql +import_if_missing tomato_ils ./config/databases/tomato_ils.sql echo "Data are now loaded. Preparing API config" echo "Please manually edit config file!" diff --git a/data/efp_info/db_source_summary.json b/data/efp_info/db_source_summary.json new file mode 100644 index 0000000..677864f --- /dev/null +++ b/data/efp_info/db_source_summary.json @@ -0,0 +1,154 @@ +{ + "actinidia_bud_development": "efp", + "actinidia_flower_fruit_development": "efp", + "actinidia_postharvest": "efp", + "actinidia_vegetative_growth": "efp", + "apple": "efp", + "arabidopsis_ecotypes": "efp", + "arachis": "efp", + "atgenexp": "efp", + "atgenexp_hormone": "both", + "atgenexp_pathogen": "both", + "atgenexp_plus": "both", + "atgenexp_stress": "both", + "barley_mas": "efp", + "barley_rma": "efp", + "barley_seed": "eplant", + "barley_spike_meristem": "eplant", + "barley_spike_meristem_v3": "eplant", + "brachypodium": "efp", + "brachypodium_Bd21": "efp", + "brachypodium_grains": "efp", + "brachypodium_metabolites_map": "efp", + "brachypodium_photo_thermocycle": "efp", + "brassica_rapa": "efp", + "cacao_developmental_atlas": "efp", + "cacao_developmental_atlas_sca": "efp", + "cacao_drought_diurnal_atlas": "efp", + "cacao_drought_diurnal_atlas_sca": "efp", + "cacao_infection": "efp", + "cacao_leaf": "efp", + "cacao_meristem_atlas_sca": "efp", + "cacao_seed_atlas_sca": "efp", + "camelina": "both", + "camelina_tpm": "efp", + "cannabis": "both", + "canola_seed": "efp", + "dna_damage": "both", + "durum_wheat_abiotic_stress": "efp", + "durum_wheat_biotic_stress": "efp", + "durum_wheat_development": "efp", + "embryo": "efp", + "eucalyptus": "eplant", + "euphorbia": "efp", + "gc_drought": "eplant", + "germination": "both", + "grape_developmental": "efp", + "guard_cell": "both", + "gynoecium": "efp", + "heterodera_schachtii": "eplant", + "human_body_map_2": "efp", + "human_developmental": "efp", + "kalanchoe": "efp", + "klepikova": "both", + "lateral_root_initiation": "efp", + "light_series": "efp", + "lipid_map": "efp", + "little_millet": "efp", + "lupin_lcm_leaf": "efp", + "lupin_lcm_pod": "efp", + "lupin_lcm_stem": "efp", + "lupin_whole_plant": "efp", + "maize_RMA_linear": "both", + "maize_atlas_v5": "efp", + "maize_buell_lab": "efp", + "maize_early_seed": "efp", + "maize_ears": "both", + "maize_embryonic_leaf_development": "efp", + "maize_enzyme": "efp", + "maize_gdowns": "both", + "maize_iplant": "both", + "maize_kernel_v5": "efp", + "maize_leaf_gradient": "both", + "maize_metabolite": "efp", + "maize_rice_comparison": "efp", + "maize_root": "both", + "maize_stress_v5": "efp", + "mangosteen_aril_vs_rind": "efp", + "mangosteen_callus": "efp", + "mangosteen_diseased_vs_normal": "efp", + "mangosteen_fruit_ripening": "efp", + "mangosteen_seed_development": "efp", + "mangosteen_seed_germination": "efp", + "marchantia_organ_stress": "efp", + "medicago_mas": "both", + "medicago_rma": "efp", + "medicago_root": "eplant", + "medicago_seed": "both", + "meristem_db": "efp", + "mouse_db": "efp", + "oat": "efp", + "phelipanche": "efp", + "physcomitrella_db": "efp", + "poplar": "both", + "poplar_leaf": "eplant", + "poplar_xylem": "eplant", + "potato_dev": "both", + "potato_stress": "both", + "rice_abiotic_stress_sc_pseudobulk": "efp", + "rice_drought_heat_stress": "efp", + "rice_leaf_gradient": "both", + "rice_maize_comparison": "efp", + "rice_mas": "both", + "rice_metabolite": "efp", + "rice_rma": "efp", + "rice_root": "eplant", + "root": "both", + "root_Schaefer_lab": "eplant", + "seed_db": "efp", + "seedcoat": "efp", + "selaginella": "efp", + "shoot_apex": "both", + "silique": "efp", + "single_cell": "both", + "sorghum_atlas_w_BS_cells": "efp", + "sorghum_developmental": "efp", + "sorghum_flowering_activation": "efp", + "sorghum_low_phosphorus": "efp", + "sorghum_phosphate_stress": "efp", + "sorghum_saline_alkali_stress": "efp", + "sorghum_stress": "efp", + "sorghum_strigolactone_variation": "efp", + "sorghum_sulfur_stress": "efp", + "sorghum_vascularization_and_internode": "efp", + "soybean": "both", + "soybean_embryonic_development": "efp", + "soybean_heart_cotyledon_globular": "efp", + "soybean_senescence": "efp", + "soybean_severin": "both", + "strawberry": "efp", + "striga": "efp", + "sugarcane_culms": "eplant", + "sugarcane_leaf": "eplant", + "sunflower": "eplant", + "thellungiella_db": "efp", + "tomato": "efp", + "tomato_ils": "both", + "tomato_ils2": "both", + "tomato_meristem": "efp", + "tomato_renormalized": "both", + "tomato_root": "eplant", + "tomato_root_field_pot": "eplant", + "tomato_s_pennellii": "both", + "tomato_seed": "efp", + "tomato_shade_mutants": "efp", + "tomato_shade_timecourse": "efp", + "triphysaria": "efp", + "triticale": "efp", + "triticale_mas": "efp", + "tung_tree": "efp", + "wheat": "both", + "wheat_abiotic_stress": "efp", + "wheat_embryogenesis": "efp", + "wheat_meiosis": "efp" +} \ No newline at end of file diff --git a/data/efp_info/efp_eplant_species_view_info.json b/data/efp_info/efp_eplant_species_view_info.json new file mode 100644 index 0000000..df49bb2 --- /dev/null +++ b/data/efp_info/efp_eplant_species_view_info.json @@ -0,0 +1,35178 @@ +{ + "efp": { + "efp_arabidopsis": [ + { + "source": "efp", + "species": "arabidopsis", + "database": "atgenexp_stress", + "view_name": "Abiotic Stress II", + "view_file": "Abiotic_Stress_II", + "groups": { + "GSM491684;GSM491685;GSM491686": { + "controls": [ + "GSM491684", + "GSM491685", + "GSM491686" + ], + "treatments": { + "Water_limited_(dry),_Pre-dawn": [ + "GSM491687", + "GSM491688", + "GSM491689" + ], + "Well_watered,_pre-dawn_(control)": [ + "GSM491684", + "GSM491685", + "GSM491686" + ] + } + }, + "GSM491672;GSM491673;GSM491674": { + "controls": [ + "GSM491672", + "GSM491673", + "GSM491674" + ], + "treatments": { + "Well_watered,_Late_day_(control)": [ + "GSM491672", + "GSM491673", + "GSM491674" + ], + "Water_limited_(dry),_Late_day": [ + "GSM491675", + "GSM491676", + "GSM491677" + ] + } + }, + "GSM237280;GSM237281": { + "controls": [ + "GSM237280", + "GSM237281" + ], + "treatments": { + "Root,_non-selenate_treated_(control)": [ + "GSM237280", + "GSM237281" + ], + "Root,_Selenate_treated": [ + "GSM237282", + "GSM237283" + ] + } + }, + "GSM491666;GSM491667;GSM491668": { + "controls": [ + "GSM491666", + "GSM491667", + "GSM491668" + ], + "treatments": { + "Water_limited_(dry),_Midday": [ + "GSM491669", + "GSM491670", + "GSM491671" + ], + "Well_watered,_Midday_(control)": [ + "GSM491666", + "GSM491667", + "GSM491668" + ] + } + }, + "GSM392492;GSM392493": { + "controls": [ + "GSM392492", + "GSM392493" + ], + "treatments": { + "Shoot,_non-selenate_treated_(control)": [ + "GSM392492", + "GSM392493" + ] + } + }, + "GSM40552": { + "controls": [ + "GSM40552" + ], + "treatments": { + "Non_Stressed_(control),_Total_RNA": [ + "GSM40552" + ], + "Hypoxia_Stress,_Total_RNA": [ + "GSM40553" + ] + } + }, + "GSM40554": { + "controls": [ + "GSM40554" + ], + "treatments": { + "Non_Stressed_(control),_Polysomal_RNA": [ + "GSM40554" + ], + "Hypoxia_Stress,_Polysomal_RNA": [ + "GSM40555" + ] + } + }, + "GSM237292;GSM237293": { + "controls": [ + "GSM237292", + "GSM237293" + ], + "treatments": { + "Shoot,_non-_selenate_treated": [ + "GSM237294", + "GSM237295" + ] + } + }, + "GSM491678;GSM491679;GSM491680": { + "controls": [ + "GSM491678", + "GSM491679", + "GSM491680" + ], + "treatments": { + "Well_watered,_midnight_(control)": [ + "GSM491678", + "GSM491679", + "GSM491680" + ], + "Water_limited_(dry),_midnight": [ + "GSM491681", + "GSM491682", + "GSM491683" + ] + } + } + } + }, + { + "source": "efp", + "species": "arabidopsis", + "database": "atgenexp_pathogen", + "view_name": "Biotic Stress II", + "view_file": "Biotic_Stress_II", + "groups": { + "GSM392490;GSM392491": { + "controls": [ + "GSM392490", + "GSM392491" + ], + "treatments": { + "Col_laser_microdissected,_5_d_UI,": [ + "GSM392490", + "GSM392491" + ], + "Col_laser_microdissected,_5_dpi": [ + "GSM392488", + "GSM392489" + ], + "eds16_laser_microdissected,_5_dpi": [ + "GSM392492", + "GSM392493" + ] + } + }, + "GSM392500;GSM392501": { + "controls": [ + "GSM392500", + "GSM392501" + ], + "treatments": { + "Col_whole_leaf_amplified,_5_d_UI": [ + "GSM392500", + "GSM392501" + ], + "Col_whole_leaf_amplified,_5_dpi,": [ + "GSM392498", + "GSM392499" + ], + "Col_leaf_scrape,_5_dpi": [ + "GSM392502", + "GSM392503" + ] + } + }, + "GSM554311_WT_Emwa1_0dpi_rep2": { + "controls": [ + "GSM554311_WT_Emwa1_0dpi_rep2" + ], + "treatments": { + "WT_Emwa1_0dpi_rep1+rep2": [ + "GSM554311_WT_Emwa1_0dpi_rep1", + "GSM554311_WT_Emwa1_0dpi_rep2" + ], + "WT_Emwa1_0.5dpi_rep1+rep2": [ + "GSM554312_WT_Emwa1_0.5dpi_rep2" + ], + "WT_Emwa1_2dpi_rep1+rep2": [ + "GSM554313_WT_Emwa1_2dpi_rep1", + "GSM554313_WT_Emwa1_2dpi_rep2" + ], + "WT_Emwa1_4dpi_rep1+rep2": [ + "GSM554314_WT_Emwa1_4dpi_rep1", + "GSM554314_WT_Emwa1_4dpi_rep2" + ], + "WT_Emwa1_6dpi_rep1+rep2": [ + "GSM554315_WT_Emwa1_6dpi_rep1", + "GSM554315_WT_Emwa1_6dpi_rep2" + ] + } + }, + "GSM554316_rpp4_Emwa1_0dpi_rep1;GSM554316_rpp4_Emwa1_0dpi_rep2": { + "controls": [ + "GSM554316_rpp4_Emwa1_0dpi_rep1", + "GSM554316_rpp4_Emwa1_0dpi_rep2" + ], + "treatments": { + "rpp4_Emwa1_0dpi_rep1+rep2": [ + "GSM554316_rpp4_Emwa1_0dpi_rep1", + "GSM554316_rpp4_Emwa1_0dpi_rep2" + ], + "rpp4_Emwa1_0.5dpi_rep1+rep2": [ + "GSM554317_rpp4_Emwa1_0.5dpi_rep1", + "GSM554317_rpp4_Emwa1_0.5dpi_rep2" + ], + "rpp4_Emwa1_2dpi_rep1+rep2": [ + "GSM554318_rpp4_Emwa1_2dpi_rep1", + "GSM554318_rpp4_Emwa1_2dpi_rep2" + ], + "rpp4_Emwa1_4dpi_rep1+rep2": [ + "GSM554319_rpp4_Emwa1_4dpi_rep1", + "GSM554319_rpp4_Emwa1_4dpi_rep2" + ], + "rpp4_Emwa1_6dpi_rep1+rep2": [ + "GSM554320_rpp4_Emwa1_6dpi_rep1", + "GSM554320_rpp4_Emwa1_6dpi_rep2" + ] + } + }, + "GSM157299;GSM157300;GSM157301": { + "controls": [ + "GSM157299_JPritchard_A-1_CTR_Rep1_ATH1", + "GSM157300_JPritchard_A-2_CTR_Rep2_ATH1", + "GSM157301_Pritchard_A-3_CTR_Rep3_ATH1" + ], + "treatments": { + "Control": [ + "GSM157299_JPritchard_A-1_CTR_Rep1_ATH1", + "GSM157300_JPritchard_A-2_CTR_Rep2_ATH1", + "GSM157301_Pritchard_A-3_CTR_Rep3_ATH1" + ], + "Aphid_infested": [ + "GSM157303_JPritchard_A-5_API_Rep2_ATH1", + "GSM157304_JPritchard_A-6_API_Rep3_ATH1" + ] + } + } + } + }, + { + "source": "efp", + "species": "arabidopsis", + "database": "atgenexp_pathogen", + "view_name": "Biotic Stress", + "view_file": "Biotic_Stress", + "groups": { + "Botrytis_cinerea_at_18_Hours": { + "controls": [ + "CT181-1", + "CT181-2", + "CT182-1" + ], + "treatments": { + "Control_B.c._at_18_Hours": [ + "CT181-1", + "CT181-2", + "CT182-1" + ], + "Treated_B.c._at_18_Hours": [ + "BC181-1", + "BC181-2", + "BC182-1" + ] + } + }, + "Botrytis_cinerea_at_48_Hours": { + "controls": [ + "CT481-1", + "CT482-1", + "CT482-2" + ], + "treatments": { + "Control_B.c._at_48_Hours": [ + "CT481-1", + "CT482-1", + "CT482-2" + ], + "Treated_B.c._at_48_Hours": [ + "BC481-1", + "BC482-1", + "BC482-2" + ] + } + }, + "Half_Leaf_Pseudomonas_syringae_at_4_Hours": { + "controls": [ + "2505", + "2795" + ], + "treatments": { + "Control_Half_P.s_at_4_Hours": [ + "2505", + "2795" + ], + "Avirulent_Half_P.s_at_4_Hours": [ + "2504", + "2796" + ], + "Virulent_Half_P.s_at_4_Hours": [ + "2530", + "2797" + ] + } + }, + "Half_Leaf_Pseudomonas_syringae_at_8_Hours": { + "controls": [ + "2507", + "2792" + ], + "treatments": { + "Control_Half_P.s_at_8_Hours": [ + "2507", + "2792" + ], + "Avirulent_Half_P.s_at_8_Hours": [ + "2506", + "2793" + ], + "Virulent_Half_P.s_at_8_Hours": [ + "2529", + "2794" + ] + } + }, + "Half_Leaf_Pseudomonas_syringae_at_16_Hours": { + "controls": [ + "2527", + "2789" + ], + "treatments": { + "Control_Half_P.s_at_16_Hours": [ + "2527", + "2789" + ], + "Avirulent_Half_P.s_at_16_Hours": [ + "2508", + "2790" + ], + "Virulent_Half_P.s_at_16_Hours": [ + "2528", + "2791" + ] + } + }, + "Half_Leaf_Pseudomonas_syringae_at_24_Hours": { + "controls": [ + "2510", + "2786" + ], + "treatments": { + "Control_Half_P.s_at_24_Hours": [ + "2510", + "2786" + ], + "Avirulent_Half_P.s_at_24_Hours": [ + "2509", + "2787" + ], + "Virulent_Half_P.s_at_24_Hours": [ + "2526", + "2788" + ] + } + }, + "Half_Leaf_Pseudomonas_syringae_at_48_Hours": { + "controls": [ + "2512", + "2783" + ], + "treatments": { + "Control_Half_P.s_at_48_Hours": [ + "2512", + "2783" + ], + "Avirulent_Half_P.s_at_48_Hours": [ + "2511", + "2784" + ], + "Virulent_Half_P.s_at_48_Hours": [ + "2525", + "2785" + ] + } + }, + "Infiltrating_Pseudomonas_syringae_at_2_Hours": { + "controls": [ + "AtGen_A-53_33-1_REP1_ATH1", + "AtGen_A-54_33-2_REP2_ATH1", + "AtGen_A-55_33-3_REP3_ATH1" + ], + "treatments": { + "Control_P.s._at_2_Hours": [ + "AtGen_A-53_33-1_REP1_ATH1", + "AtGen_A-54_33-2_REP2_ATH1", + "AtGen_A-55_33-3_REP3_ATH1" + ], + "Virulent_P.s._at_2_Hours": [ + "AtGen_A-5_21-1_REP1_ATH1", + "AtGen_A-6_21-2_REP2_ATH1", + "AtGen_A-8_21-4_REP3_ATH1" + ], + "Avirulent_P.s._at_2_Hours": [ + "AtGen_A-17_24-1_REP1_ATH1", + "AtGen_A-18_24-2_REP2_ATH1", + "AtGen_A-19_24-3_REP3_ATH1" + ], + "Deficient_P.s._at_2_Hours": [ + "AtGen_A-29_27-1_REP1_ATH1", + "AtGen_A-30_27-2_REP2_ATH1", + "AtGen_A-31-27-3_REP3_ATH1" + ], + "Nonhost_P.s._at_2_Hours": [ + "AtGen_A-41_30-1_REP1_ATH1", + "AtGen_A-42_30-2_REP2_ATH1", + "AtGen_A-43_30-3_REP3_ATH1" + ] + } + }, + "Infiltrating_Pseudomonas_syringae_at_6_Hours": { + "controls": [ + "AtGen_A-58_34-2_REP1_ATH1", + "AtGen_A-59_34-3_REP2_ATH1", + "AtGen_A-60_34-4_REP3_ATH1" + ], + "treatments": { + "Control_P.s._at_6_Hours": [ + "AtGen_A-58_34-2_REP1_ATH1", + "AtGen_A-59_34-3_REP2_ATH1", + "AtGen_A-60_34-4_REP3_ATH1" + ], + "Virulent_P.s._at_6_Hours": [ + "AtGen_A-9_22-1_REP1_ATH1", + "AtGen_A-10_22-2_REP2_ATH1", + "AtGen_A-11_22-3_REP3_ATH1" + ], + "Avirulent_P.s._at_6_Hours": [ + "AtGen_A-21_25-1_REP1_ATH1", + "AtGen_A-23_25-3_REP2_ATH1", + "AtGen_A-24_25-4_REP3_ATH1" + ], + "Deficient_P.s._at_6_Hours": [ + "AtGen_A-33_28-1_REP1_ATH1", + "AtGen_A-34_28-2_REP2_ATH1", + "AtGen_A-35_28-3_REP3_ATH1" + ], + "Nonhost_P.s._at_6_Hours": [ + "AtGen_A-45_31-1_REP1_ATH1", + 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"Circadian_experiment_-_plants_grown_under_12h_light-dark_cycle_with_a_temperature_cycle,_then_sampled_under_continuous_light_and_constant_temperature,_44h": [ + "LL_LDHC_44" + ] + } + }, + "LL_LDHH_SH_00": { + "controls": [ + "LL_LDHH_SH_00" + ], + "treatments": { + "Circadian_experiment_-_plants_grown_under_12h_light-dark_cycle_and_constant_temperature,_then_sampled_under_continuous_light_and_constant_temperature,_0h": [ + "LL_LDHH_SH_00" + ], + "Circadian_experiment_-_plants_grown_under_12h_light-dark_cycle_and_constant_temperature,_then_sampled_under_continuous_light_and_constant_temperature,_4h": [ + "LL_LDHH_SH_04" + ], + "Circadian_experiment_-_plants_grown_under_12h_light-dark_cycle_and_constant_temperature,_then_sampled_under_continuous_light_and_constant_temperature,_8h": [ + "LL_LDHH_SH_08" + ], + "Circadian_experiment_-_plants_grown_under_12h_light-dark_cycle_and_constant_temperature,_then_sampled_under_continuous_light_and_constant_temperature,_12h": [ + "LL_LDHH_SH_12" + 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"Circadian_experiment_-_plants_grown_under_12h_light-dark_cycle_and_constant_temperature,_then_sampled_under_continuous_light_and_constant_temperature,_28h": [ + "LL_LDHH_AM_54" + ], + "Circadian_experiment_-_plants_grown_under_12h_light-dark_cycle_and_constant_temperature,_then_sampled_under_continuous_light_and_constant_temperature,_32h": [ + "LL_LDHH_AM_58" + ], + "Circadian_experiment_-_plants_grown_under_12h_light-dark_cycle_and_constant_temperature,_then_sampled_under_continuous_light_and_constant_temperature,_36h": [ + "LL_LDHH_AM_62" + ], + "Circadian_experiment_-_plants_grown_under_12h_light-dark_cycle_and_constant_temperature,_then_sampled_under_continuous_light_and_constant_temperature,_40h": [ + "LL_LDHH_AM_66" + ], + "Circadian_experiment_-_plants_grown_under_12h_light-dark_cycle_and_constant_temperature,_then_sampled_under_continuous_light_and_constant_temperature,_44h": [ + "LL_LDHH_AM_70" + ] + } + }, + "DD_DDHC_00": { + "controls": [ + "DD_DDHC_00" + ], + "treatments": { + "Control_series_-_plants_grown_in_constant_dark_but_with_a_temperature_cycle_applied._Samples_taken_in_constant_dark_and_temperature,_0h": [ + "DD_DDHC_00" + ], + "Control_series_-_plants_grown_in_constant_dark_but_with_a_temperature_cycle_applied._Samples_taken_in_constant_dark_and_temperature,_4h": [ + "DD_DDHC_04" + ], + "Control_series_-_plants_grown_in_constant_dark_but_with_a_temperature_cycle_applied._Samples_taken_in_constant_dark_and_temperature,_8h": [ + "DD_DDHC_08" + ], + "Control_series_-_plants_grown_in_constant_dark_but_with_a_temperature_cycle_applied._Samples_taken_in_constant_dark_and_temperature,_12h": [ + "DD_DDHC_12" + ], + "Control_series_-_plants_grown_in_constant_dark_but_with_a_temperature_cycle_applied._Samples_taken_in_constant_dark_and_temperature,_16h": [ + "DD_DDHC_16" + ], + "Control_series_-_plants_grown_in_constant_dark_but_with_a_temperature_cycle_applied._Samples_taken_in_constant_dark_and_temperature,_20h": [ + "DD_DDHC_20" + ], + 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} + }, + "Vegetative_Bud": { + "controls": [ + "MED_CTRL", + "MED_CTRL" + ], + "treatments": { + "Vegetative_Bud": [ + "Vegetative Bud_rep1", + "Vegetative Bud_rep2", + "Vegetative Bud_rep3" + ] + } + }, + "Petiole": { + "controls": [ + "MED_CTRL", + "MED_CTRL" + ], + "treatments": { + "Petiole": [ + "Petiole_rep1", + "Petiole_rep2", + "Petiole_rep3" + ] + } + }, + "Stem": { + "controls": [ + "MED_CTRL", + "MED_CTRL" + ], + "treatments": { + "Stem": [ + "Stem_rep1", + "Stem_rep2", + "Stem_rep3" + ] + } + }, + "Leaf_with_Petiolules": { + "controls": [ + "MED_CTRL", + "MED_CTRL" + ], + "treatments": { + "Leaf_with_Petiolules": [ + "Leaf_rep1", + "Leaf_rep2", + "Leaf_rep3" + ] + } + }, + "Root": { + "controls": [ + "MED_CTRL", + "MED_CTRL" + ], + "treatments": { + "Root": [ + "Root_rep1", + "Root_rep2", + "Root_rep3" + ] + } + }, + "Non-inoculated_root": { + "controls": [ + "MED_CTRL", + "MED_CTRL" + ], + "treatments": { + "Non-inoculated_root": [ + "Root0d_rep1", + "Root0d_rep2", + "Root0d_rep3" + ] + } + } + } + } + ], + "eplant_eucalyptus": [ + { + "source": "eplant", + "project": "eplant_eucalyptus", + "species": "Eucalyptus_grandis", + "family": "experiment", + "database": "eucalyptus", + "view_name": "Stress", + "view_folder": "Stress", + "groups": { + "Leaf": { + "controls": [ + "Leaf_Mock_rep1", + "Leaf_Mock_rep2", + "Leaf_Mock_rep3" + ], + "treatments": { + "Leaf_-_Control": [ + "Leaf_Mock_rep1", + "Leaf_Mock_rep2", + "Leaf_Mock_rep3" + ], + "Leaf_-_Salicylic_Acid_1h": [ + "Leaf_SA_1h_rep1", + "Leaf_SA_1h_rep2", + "Leaf_SA_1h_rep3" + ], + "Leaf_-_Salicylic_Acid_6h": [ + "Leaf_SA_6h_rep1", + "Leaf_SA_6h_rep2", + "Leaf_SA_6h_rep3" + ], + "Leaf_-_Salicylic_Acid_24h": [ + "Leaf_SA_24h_rep1", + "Leaf_SA_24h_rep2", + "Leaf_SA_24h_rep3" + ], + "Leaf_-_Salicylic_Acid_168h": [ + "Leaf_SA_168h_rep1", + "Leaf_SA_168h_rep2", + "Leaf_SA_168h_rep3" + ], + "Leaf_-_Methyl_Jasmonate_1h": [ + "Leaf_JA_1h_rep1", + "Leaf_JA_1h_rep2", + "Leaf_JA_1h_rep3" + ], + 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"Root_Bdef_21d_rep2", + "Root_Bdef_21d_rep3" + ] + } + }, + "Shoot": { + "controls": [ + "Shoot_Mock_rep1", + "Shoot_Mock_rep2", + "Shoot_Mock_rep3" + ], + "treatments": { + "Shoot_-_Control": [ + "Shoot_Mock_rep1", + "Shoot_Mock_rep2", + "Shoot_Mock_rep3" + ], + "Shoot_-_Phosphate_deficiency_6h": [ + "Shoot_Pidef_6h_rep1", + "Shoot_Pidef_6h_rep2", + "Shoot_Pidef_6h_rep3" + ], + "Shoot_-_Phosphate_deficiency_24h": [ + "Shoot_Pidef_24h_rep1", + "Shoot_Pidef_24h_rep2", + "Shoot_Pidef_24h_rep3" + ], + "Shoot_-_Phosphate_deficiency_48h": [ + "Shoot_Pidef_48h_rep1", + "Shoot_Pidef_48h_rep2", + "Shoot_Pidef_48h_rep3" + ], + "Shoot_-_Phosphate_deficiency_96h": [ + "Shoot_Pidef_96h_rep1", + "Shoot_Pidef_96h_rep2", + "Shoot_Pidef_96h_rep3" + ], + "Shoot_-_Phosphate_deficiency_21d": [ + "Shoot_Pidef_21d_rep1", + "Shoot_Pidef_21d_rep2", + "Shoot_Pidef_21d_rep3" + ], + "Shoot_-_Boron_deficiency_6h": [ + "Shoot_Bdef_6h_rep1", + "Shoot_Bdef_6h_rep2", + "Shoot_Bdef_6h_rep3" + ], + 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+ "proj_ids": [ + "1", + "2" + ] + }, + "Fruit": { + "n_view_samples": 6, + "n_matched_in_real_data_sample": 5, + "proj_ids": [ + "1" + ] + }, + "Plant": { + "n_view_samples": 15, + "n_matched_in_real_data_sample": 13, + "proj_ids": [ + "2" + ] + } + } + } + }, + "tomato_root": { + "source": "eplant", + "platform": "rna_seq", + "views": { + "eplant_tomato": [ + "Root" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "tomato_root_field_pot": { + "source": "eplant", + "platform": "rna_seq", + "views": { + "eplant_tomato": [ + "RootFieldPot" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "tomato_s_pennellii": { + "source": "both", + "platform": "rna_seq", + "views": { + "efp_tomato": [ + "M82 S pennellii Atlases Koenig et al" + ], + "eplant_tomato": [ + "TomatoAtlases" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + }, + "proj_id_breakdown": { + "classification": "duplicate_view_names", + "views": { + "M82 S pennellii Atlases Koenig et al": { + "n_view_samples": 17, + "n_matched_in_real_data_sample": 12, + "proj_ids": [ + "1" + ] + }, + "TomatoAtlases": { + "n_view_samples": 17, + "n_matched_in_real_data_sample": 12, + "proj_ids": [ + "1" + ] + } + } + } + }, + "tomato_seed": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_tomato": [ + "SEED Lab Angers" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "tomato_shade_mutants": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_tomato": [ + "Shade Mutants" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "tomato_shade_timecourse": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_tomato": [ + "Shade Timecourse WT" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "tomato_trait": { + "source": "legacy_not_in_dropdown", + "platform": "rna_seq", + "views": {}, + "validation": { + "n_samples": 16, + "n_pass": 16, + "n_fail": 0 + } + } + }, + "triphysaria": { + "triphysaria": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_triphysaria": [ + "Triphysaria" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + } + }, + "triticale": { + "triticale": { + "source": "efp", + "platform": "microarray", + "views": { + "efp_triticale": [ + "triticale" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "triticale_mas": { + "source": "efp", + "platform": "microarray", + "views": { + "efp_triticale": [ + "triticale mas" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + } + }, + "tung_tree": { + "tung_tree": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_tung_tree": [ + "Tung Tree" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + } + }, + "wheat": { + "durum_wheat_abiotic_stress": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_durum_wheat": [ + "Abiotic Stress" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "durum_wheat_biotic_stress": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_durum_wheat": [ + "Biotic Stress" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "durum_wheat_development": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_durum_wheat": [ + "Development" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "wheat": { + "source": "both", + "platform": "rna_seq", + "views": { + "efp_wheat": [ + "Developmental Atlas" + ], + "eplant_wheat": [ + "EarlyStages", + "MiddleStages", + "LateStages" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + }, + "proj_id_breakdown": { + "classification": "duplicate_view_names", + "views": { + "Developmental Atlas": { + "n_view_samples": 209, + "n_matched_in_real_data_sample": 26, + "proj_ids": [ + "1" + ] + }, + "EarlyStages": { + "n_view_samples": 61, + "n_matched_in_real_data_sample": 9, + "proj_ids": [ + "1" + ] + }, + "MiddleStages": { + "n_view_samples": 88, + "n_matched_in_real_data_sample": 11, + "proj_ids": [ + "1" + ] + }, + "LateStages": { + "n_view_samples": 62, + "n_matched_in_real_data_sample": 6, + "proj_ids": [ + "1" + ] + } + } + } + }, + "wheat_abiotic_stress": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_wheat": [ + "Wheat Abiotic Stress" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "wheat_embryogenesis": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_wheat": [ + "Wheat Embryogenesis" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "wheat_meiosis": { + "source": "efp", + "platform": "rna_seq", + "views": { + "efp_wheat": [ + "Wheat Meiosis" + ] + }, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + }, + "wheat_root": { + "source": "legacy_not_in_dropdown", + "platform": "rna_seq", + "views": {}, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + } + }, + "willow": { + "willow": { + "source": "legacy_not_in_dropdown", + "platform": "rna_seq", + "views": {}, + "validation": { + "n_samples": 30, + "n_pass": 30, + "n_fail": 0 + } + } + } +} \ No newline at end of file diff --git a/db_regex_coverage_report.csv b/db_regex_coverage_report.csv new file mode 100644 index 0000000..0b43185 --- /dev/null +++ b/db_regex_coverage_report.csv @@ -0,0 +1,194 @@ +database,source,in_master_list,has_species_mapping,has_efp_project_override,n_samples,n_pass,n_fail,looks_like_probeset,failing_ids +actinidia_bud_development,efp,True,True,False,30,30,0,False, +actinidia_flower_fruit_development,efp,True,True,False,30,30,0,False, +actinidia_postharvest,efp,True,True,False,30,30,0,False, 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+brachypodium_grains,efp,True,True,False,30,30,0,False, +brachypodium_metabolites_map,efp,True,True,True,20,20,0,False, +brachypodium_photo_thermocycle,efp,True,True,False,30,30,0,False, +brassica_rapa,efp,True,True,False,30,30,0,False, +brassica_rapa_developmental_atlas,legacy_not_in_dropdown,False,True,False,30,30,0,False, +cacao_developmental_atlas,efp,True,True,False,30,30,0,False, +cacao_developmental_atlas_sca,efp,True,True,False,30,30,0,False, +cacao_drought_diurnal_atlas,efp,True,True,False,30,30,0,False, +cacao_drought_diurnal_atlas_sca,efp,True,True,False,30,30,0,False, +cacao_infection,efp,True,True,False,30,30,0,False, +cacao_leaf,efp,True,True,False,30,30,0,False, +cacao_meristem_atlas_sca,efp,True,True,False,30,30,0,False, +cacao_seed_atlas_sca,efp,True,True,False,30,30,0,False, +camelina,both,True,True,False,30,30,0,False, +camelina_tpm,efp,True,True,False,30,30,0,False, +cannabis,both,True,True,False,30,30,0,False, 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+mangosteen_seed_germination,efp,True,True,False,30,30,0,False, +marchantia_organ_stress,efp,True,True,False,30,30,0,False, +medicago_mas,both,True,True,True,30,30,0,True, +medicago_rma,efp,True,True,True,30,30,0,True, +medicago_root,eplant,True,True,False,30,30,0,False, +medicago_root_v5,legacy_not_in_dropdown,False,True,False,30,30,0,False, +medicago_seed,both,True,True,False,30,30,0,False, +meristem_db,efp,True,True,True,30,30,0,True, +meristem_db_new,legacy_not_in_dropdown,False,True,True,30,30,0,True, +mouse_db,efp,True,True,False,30,30,0,False, +oat,efp,True,True,False,30,30,0,False, +phelipanche,efp,True,True,False,30,30,0,False, +physcomitrella_db,efp,True,True,True,30,30,0,False, +poplar,both,True,True,True,30,30,0,True, +poplar_hormone,legacy_not_in_dropdown,False,True,True,30,30,0,False, +poplar_leaf,eplant,True,True,False,30,30,0,False, +poplar_xylem,eplant,True,True,False,30,30,0,False, +potato_dev,both,True,True,False,30,30,0,False, +potato_stress,both,True,True,False,30,30,0,False, +potato_wounding,legacy_not_in_dropdown,False,True,False,30,30,0,False, +quinoa_nutrient,legacy_not_in_dropdown,False,True,False,30,30,0,False, +rice_abiotic_stress_sc_pseudobulk,efp,True,True,False,30,30,0,False, +rice_drought_heat_stress,efp,True,True,False,30,30,0,False, +rice_leaf_gradient,both,True,True,False,30,30,0,False, +rice_maize_comparison,efp,True,True,False,30,30,0,False, +rice_mas,both,True,True,True,30,30,0,True, +rice_metabolite,efp,True,True,True,20,20,0,False, +rice_rma,efp,True,True,True,30,30,0,True, +rice_root,eplant,True,True,False,30,30,0,False, +rohan,legacy_not_in_dropdown,False,True,True,30,30,0,True, +root,both,True,True,True,30,30,0,True, +root_Schaefer_lab,eplant,True,True,False,29,29,0,False, +rpatel,legacy_not_in_dropdown,False,True,True,29,29,0,True, +seed_db,efp,True,True,True,30,30,0,True, +seedcoat,efp,True,True,True,30,29,1,True,Print control plate +selaginella,efp,True,True,False,30,30,0,False, +shoot_apex,both,True,True,False,30,30,0,False, +silique,efp,True,True,False,30,30,0,False, +single_cell,both,True,True,False,30,30,0,False, +sorghum_atlas_w_BS_cells,efp,True,True,False,30,30,0,False, +sorghum_comparative_transcriptomics,legacy_not_in_dropdown,False,True,False,30,30,0,False, +sorghum_developmental,efp,True,True,False,30,30,0,False, +sorghum_developmental_2,legacy_not_in_dropdown,False,True,False,30,30,0,False, +sorghum_flowering_activation,efp,True,True,False,30,30,0,False, +sorghum_low_phosphorus,efp,True,True,False,30,30,0,False, +sorghum_nitrogen_stress,legacy_not_in_dropdown,False,True,False,30,30,0,False, +sorghum_nitrogen_use_efficiency,legacy_not_in_dropdown,False,True,False,30,30,0,False, +sorghum_phosphate_stress,efp,True,True,False,30,30,0,False, +sorghum_plasma,legacy_not_in_dropdown,False,True,False,30,30,0,False, +sorghum_saline_alkali_stress,efp,True,True,False,30,30,0,False, +sorghum_stress,efp,True,True,False,30,30,0,False, +sorghum_strigolactone_variation,efp,True,True,False,30,30,0,False, +sorghum_sulfur_stress,efp,True,True,False,30,30,0,False, +sorghum_temperature_stress,legacy_not_in_dropdown,False,True,False,30,30,0,False, +sorghum_vascularization_and_internode,efp,True,True,False,30,30,0,False, +soybean,both,True,True,False,30,30,0,False, +soybean_embryonic_development,efp,True,True,False,30,30,0,False, +soybean_heart_cotyledon_globular,efp,True,True,False,30,30,0,False, +soybean_senescence,efp,True,True,False,30,30,0,False, +soybean_severin,both,True,True,False,30,30,0,False, +spruce,legacy_not_in_dropdown,False,True,False,30,30,0,False, +strawberry,efp,True,True,False,30,30,0,False, +striga,efp,True,True,False,30,30,0,False, +sugarcane_culms,eplant,True,True,False,30,30,0,False, +sugarcane_leaf,eplant,True,True,False,30,30,0,False, +sunflower,eplant,True,True,False,30,30,0,False, +thellungiella_db,efp,True,True,True,30,30,0,False, +tomato,efp,True,True,True,30,30,0,False, +tomato_ils,both,True,True,False,30,30,0,False, +tomato_ils2,both,True,True,False,30,30,0,False, +tomato_ils3,legacy_not_in_dropdown,False,True,False,30,30,0,False, +tomato_meristem,efp,True,True,False,30,30,0,False, +tomato_renormalized,both,True,True,True,30,30,0,False, +tomato_root,eplant,True,True,False,30,30,0,False, +tomato_root_field_pot,eplant,True,True,False,30,30,0,False, +tomato_s_pennellii,both,True,True,False,30,30,0,False, +tomato_seed,efp,True,True,False,30,30,0,False, +tomato_shade_mutants,efp,True,True,False,30,30,0,False, +tomato_shade_timecourse,efp,True,True,False,30,30,0,False, +tomato_trait,legacy_not_in_dropdown,False,True,True,16,16,0,False, +triphysaria,efp,True,True,False,30,30,0,False, +triticale,efp,True,True,True,30,30,0,True, +triticale_mas,efp,True,True,True,30,30,0,True, +tung_tree,efp,True,True,False,30,30,0,False, +wheat,both,True,True,False,30,30,0,False, +wheat_abiotic_stress,efp,True,True,False,30,30,0,False, +wheat_embryogenesis,efp,True,True,False,30,30,0,False, +wheat_meiosis,efp,True,True,False,30,30,0,False, +wheat_root,legacy_not_in_dropdown,False,True,False,30,30,0,False, +willow,legacy_not_in_dropdown,False,True,False,30,30,0,False, diff --git a/efp_regex_audit_prod.csv b/efp_regex_audit_prod.csv new file mode 100644 index 0000000..8191286 --- /dev/null +++ b/efp_regex_audit_prod.csv @@ -0,0 +1,60 @@ +project,inputRegEx +efp,"^([Aa][Tt][12345CM][Gg][0-9]{5})$|^([0-9]{6}(_[xsfi])?_at)$|^([0-9]{6,9})$" +efp_Eutrema,^(Thhalv\d{8}m\.g)$|^(XLOC_\d{6})$|^(nXLOC\d{6})$|^(At\dg\d{5})$ +efp_actinidia,"^(Acc\d+\.\d{0,3})$" +efp_apple,"^(MfusH1_\d\dg\d{1,8})$" +efp_arabidopsis,"^([Aa][Tt][12345CM][Gg][0-9]{5})$|^([0-9]{6}(_[xsfi])?_at)$|^([0-9]{6,9})$" +efp_arabidopsis_lipid,"^[a-z0-9\s:;\/\[\]_\+\-]{1,64}$" +efp_arachis,^(Adur\d+_comp\d+_c\d+_seq\d+)$|^(Gyn_Aipa_c\d+_g\d+_i\d+)$|^(Aipa\d+_comp\d+_c\d+_seq\d+)$ +efp_barley,"^((HM|HV).*)$|^(HV.*_at)$|^(([0-9]{4,7})_(Reg|R)_([0-9]{2,4})-([0-9]{4})_at)$|^([0-9]{4,5}\.AF[0-9]{5}(_|_x_)at)$|^(A[0-9]{5}\.[0-9]{1}(_|_x_|_s_)at)$|^(([A-Z]{2}[0-9]{6}|[A-Z]{2}[0-9]{6}\.1)(_|_x_|_s_|_CDS-[0-9]{1,2}_|_CDS-[0-9]{1,2}_s_)at)$|^(AFFX-(BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX)-(3|5|M)_at)$|^(AFFX-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre)-(3|5|M)(_|_x_|_s_)at)$|^(ChlorContig[0-9]{1,2}(_|_x_|_s_)at)$|^(((MitoContig|Contig)[0-9]{1,6})(_|_x_|_s_)at)$|^(D[0-9]{5}_at)$|^(Dhn[0-9]{2}\(Morex\)(_|_s_)at)$|^(E(Ban|Bca|Bed|Bem|Bes|Bma|Bpi|Bro)[0-9]{2}_SQ[0-9]{3}_[A-Z]{1}[0-9]{2}(_|_s_|_x_)at)$|^(Franka(_|_b_)3pri[0-9]{1,2}(_|_s_|_x_)at)$|^(H[A-Z]{1}[0-9]{1-4}[A-Z]{1}[0-9]{1,2}[a-z]{1}(_|_x_|_s_)at)$|^(HVSME[a-z]{1}[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f)(_|_x_|_s_)at)$|^(HV_CEa[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f)(_|_x_|_s_)at)$|^(H[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{2}r(_|_x_|_s_)at)$|^(Mla([0-9]{1,2}|[0-9]{1,2}DH)(_orf_|_div5_|_5pri_|_5pri-|_consrvd_|_3pri12_)(3pri12|3pr|UTR_intron2|UTR_intron1|5pri_end)(_|_x_|_s_)at)$|^((Mla|Mlk)(_div5|_3pri12)(_|_x_|_s__at))$|^(S[0-9]{10}[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{1}(_|_x_|_s_)at)$|^((b|rb)(aak|aal|ags|ah|asd)[0-9]{1,2}[a-z]{1}[0-9]{2}(_|_x_|_s_)at)$|^(([0-9]{4,7})_(Reg|R)_([0-9]{2,4})-([0-9]{4}))$|^([0-9]{4,5}\.AF[0-9]{5})$|^(A[0-9]{5}\.[0-9]{1})$|^([A-Z]{2}[0-9]{6}|[A-Z]{2}[0-9]{6}\.1)$|^(AFFX-(BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX))$|^(AFFX-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre))$|^(ChlorContig[0-9]{1,2})$|^((MitoContig|Contig)[0-9]{1,6})$|^(D[0-9]{5})$|^(Dhn[0-9]{2}\(Morex\))$|^(E(Ban|Bca|Bed|Bem|Bes|Bma|Bpi|Bro)[0-9]{2}_SQ[0-9]{3}_[A-Z]{1}[0-9]{2})$|^(Franka(_|_b_)3pri[0-9]{1,2})$|^(H[A-Z]{1}[0-9]{1-4}[A-Z]{1}[0-9]{1,2}[a-z]{1})$|^(HVSME[a-z]{1}[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f))$|^(HV_CEa[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f))$|^(H[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{2}r)$|^(Mla([0-9]{1,2}|[0-9]{1,2}DH)(_orf_|_div5_|_5pri_|_5pri-|_consrvd_|_3pri12_)(3pri12|3pr|UTR_intron2|UTR_intron1|5pri_end))$|^((Mla|Mlk)(_div5|_3pri12))$|^(S[0-9]{10}[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{1})$|^((b|rb)(aak|aal|ags|ah|asd)[0-9]{1,2}[a-z]{1}[0-9]{2})$|^(HO)$|^(MLOC\.[0-9]{4,6}\.[0-9]{1,2})$|^(AK[0-9]{6}\.1)$|^(AJ[0-9]{6}\.1)$" +efp_brachypodium,^(Bradi\d+g\d+.\d)$|^(Bradi\d+s\d+.\d)$|^(Bradi\d+.g\d+)$ +efp_brachypodium_metabolites,"^[a-z\s]{0,40}$" +efp_brassica_rapa,"^(Bra.\d+g\d{0,10})$" +efp_cacao_ccn,"^(CCN-51_Chr\d{1,3}v\d{1,3}_\d{1,9})$" +efp_cacao_sca,"^(SCA-6_Chr\d{1,3}v\d{1,3}_\d{1,9})$" +efp_cacao_tc,^(Tc\d+v2_g\d+)$ +efp_camelina,"^(Csa\d{0,5}[gs]\d{0,6}.\d{0,3})$|^(At\d[cgm]\d{0,6})$" +efp_cannabis,(^C\d+$)|(^scaffold\d+$)|(^AGQN\d+$) +efp_canola,"^(Bna\D\d{1,3}g\d{1,8}\D)$|^(Bna\Dnng\d{1,8}\D)$" +efp_durum_wheat,"^(TrturSVE\d\D\d{1,3}G\d{1,12})$|^(TrturSVE\d\D\d{1,3}G\d{1,12}_ncBOCREA)$" +efp_euphorbia,"^(Ep_chr\d_g\d{1,8})$" +efp_eutrema,^(Thhalv\d{8}m\.g)$|^(XLOC_\d{6})$|^(nXLOC\d{6})$|^(At\dg\d{5})$ +efp_grape,"^(VIT_\d{1,2}s\d{4}g\d{5})$|^CHRUN[a-z0-9_]{1,20}$|^CHR\d{1,2}[a-z0-9_]{1,2}$" +efp_human,"^(\D{0,12}\d{0,12})$|^(\d{1,12})$" +efp_kalanchoe,^(Kaladp\d+s\d+)$ +efp_little_millet,^(TRINITY_DN\d+_c\d+_g\d+_i\d+)$ +efp_lupin,"^(Luan_Oskar_.{1,12}_\d{1,12})$" +efp_maize,"^(AC[0-9]{6}\.[0-9]{1}_FG[0-9]{3})$|^(AC[0-9]{6}\.[0-9]{1}_FGT[0-9]{3})$|^(GRMZM(2|5)G[0-9]{6})$|^(GRMZM(2|5)G[0-9]{6}_T[0-9]{2})$|^(Zm\d+d\d+)$|^(Zm\d{1,10}eb\d{1,10})$" +efp_maize_enzyme,"^[a-z\-\(\)\s]{0,37}$" +efp_maize_metabolite,"^[a-z0-9,\s\-\(\)]{0,40}$" +efp_maize_transcriptomics,"^(AC[0-9]{6}\.[0-9]{1}_FG[0-9]{3})$|^(AC[0-9]{6}\.[0-9]{1}_FGT[0-9]{3})$|^(GRMZM(2|5)G[0-9]{6})$|^(GRMZM(2|5)G[0-9]{6}_T[0-9]{2})$|^(Zm\d+d\d+)$|^(Zm\d{1,10}eb\d{1,10})$" +efp_mangosteen,"^(DN\d{1,10})$" +efp_marchantia,"^(Mp.{1,3}g\d{1,7}\.?\d{1,3}?)$" +efp_medicago,"^(Medtr\d{1}g\d{6})$|^(Medtr\d{1}g\d{6}\.[0-9]{1})$|^(Mtr.\d{4,5}.1.[S1|S1_x|s1|s1_x]_at)$|^(AFFX-[Bio|Cre|Dap|Lys|Phe|Thr|Trpn][B|C|Dn|X]-[3|5|M]_at)$|^(AFFX-[Msa|Mtr]-[actin|gapc|gsta|ubq11|TrpnX]-[3|5|M]_[at|x_at|s_at])$|^(AFFX-Mtr|AFFX-r2-[Bs|Ec|P1]-[cre|dap|lys|phe|thr|bioB|bioC|bioD]-[3|5|M]_[at|s_at|x_at])$|^(AFFX-Mtr-ubq11-[3|5|M]_[at|s_at|x_at])$|^(AFFX-r2-Tag[A-Z]{1,2}_at|-3_at|-5_at|-M_at)$|^(Medtr_v1_\d{6})$" +efp_oat,"(^N0\.HOG\d{1,10}$|^\D{1,10}\.*\d{1,10}.{1,10}\d{1,10}$)" +efp_phelipanche,"^(OrAeBC\d+_\d+\.\d{1,5})|(At\d[gcm]\d{1,6})$" +efp_physcomitrella,^(Pp)\d+s\d+_\d+V\d\.\d$|^Phypa_\d+$ +efp_poplar,"^(Ptp(Affx)?\.\d{1,6}\.\d{1,6}\.(A1|A2|S1|S2)_(x_at|s_at|at|a_at))$|^((eugene3)\.e{6,12})$|^((estExt_)(Genewise|fgenesh)(1|4)\_(v1|kg|pg|pm)(\.|\_v1\.)C_LG_\w{6,10})$|^((grail3.)\d{8,12})$|^((fgenesh)(1|4)\_(kg|pg|pm)\.C\_(scaffold|LG)\_\w{7,12})$|^((gw1)\.\w{1,6}\.\w{1,4}\.1)$|^((POPTR)\_[0-9]{4}s[0-9]{5}\.*[1-5]{0,1})$|^(Potri\.[0-9]{3}G[0-9]{6}\.[0-9]{1})$" +efp_potato,^(PGSC0003DMG4\d{8})$ +efp_rice,"^(LOC_Os[0-9]{2}g[0-9]{5})$|^((AFFX|AFFX-Os)(-|_)(Ubiquitin|Actin|Cyph|Gapdh|BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX|ef1a|gapdh)(-|_)(3|5|M)_(at|x_at|s_at))$|^(AFFX-OS-(18SrRNA|25SrRNA|5.8SrRNA)_(s_at|at))$|^((AFFX-Mgr-(actin|ef1a|gapdh)-(3|5|M))_(at|x_at|s_at))$|^(AFFX-r2-Tag(A|B|C|D|E|F|G|H)_at)$|^(AFFX-r2-Tag(IN|I|J|O|Q)-(3|5|M)_at)$|^((AFFX|AFFX-Os)-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre)-(3|5|M)(_|_x_|_s_)at)$|^((Os|OsAffx)\.[0-9]{1,5}\.[0-9]{1}\.(S1|A1|S2)_(at|x_at|s_at|a_at))$" +efp_rice_metabolite,"^[a-z0-9,\s\-]{0,30}$" +efp_rice_transcriptomics,"^(LOC_Os[0-9]{2}g[0-9]{5})$|^((AFFX|AFFX-Os)(-|_)(Ubiquitin|Actin|Cyph|Gapdh|BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX|ef1a|gapdh)(-|_)(3|5|M)_(at|x_at|s_at))$|^(AFFX-OS-(18SrRNA|25SrRNA|5.8SrRNA)_(s_at|at))$|^((AFFX-Mgr-(actin|ef1a|gapdh)-(3|5|M))_(at|x_at|s_at))$|^(AFFX-r2-Tag(A|B|C|D|E|F|G|H)_at)$|^(AFFX-r2-Tag(IN|I|J|O|Q)-(3|5|M)_at)$|^((AFFX|AFFX-Os)-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre)-(3|5|M)(_|_x_|_s_)at)$|^((Os|OsAffx)\.[0-9]{1,5}\.[0-9]{1}\.(S1|A1|S2)_(at|x_at|s_at|a_at))$" +efp_seedcoat,"^(At[12345CM]g[0-9]{5})$|^([0-9]{6}(_[xsfi])?_at)$|^([0-9]{6,9})$|^(\D\d+_\d+)$" +efp_selaginella,^(Smo\d+)$ +efp_sorghum,"^(Sobic.\d{0,5}G\d{0,10}$|^Sobic.K\d{0,10}$|^ENSRNA\d{0,12}$|^SORBI_\d{1,6}G\d{1,10})$" +efp_soybean,"^((Glyma\d{1,3}g\d{1,6}\.?\d?)$|^(Glyma\.\d{1,3}g\d{1,8}))$" +efp_strawberry,"^(FvH4_c?\d{1,3}g\d{1,7})$|^(gene\d{1,10})$" +efp_striga,"^(StHeBC3\_\d+\.\d{1,5})$|^(At\d[gcm]\d{1,6})$" +efp_tomato,"^(Solyc\d{2}g\d{6}\.?\d{0,3})$|^(TU\d{6})$" +efp_triphysaria,"^(TrVeBC\d+_\d+\.\d{1,5})$|^(At\d[gcm]\d{1,6})$" +efp_triticale,^(Ta.\d+.\d+.\D+\d+_at)$ +efp_tung_tree,^(Vf\d+G\d+)$ +efp_wheat,"^(TraesCS\d\D\d{0,2}[G]\d{0,6}L*C*\.*\d*)$|^(TraesCSU\d+G\d+L*C*\.*\d*)$" +efpbarley,"^((HM|HV).*)$|^(HV.*_at)$|^(([0-9]{4,7})_(Reg|R)_([0-9]{2,4})-([0-9]{4})_at)$|^([0-9]{4,5}\.AF[0-9]{5}(_|_x_)at)$|^(A[0-9]{5}\.[0-9]{1}(_|_x_|_s_)at)$|^(([A-Z]{2}[0-9]{6}|[A-Z]{2}[0-9]{6}\.1)(_|_x_|_s_|_CDS-[0-9]{1,2}_|_CDS-[0-9]{1,2}_s_)at)$|^(AFFX-(BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX)-(3|5|M)_at)$|^(AFFX-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre)-(3|5|M)(_|_x_|_s_)at)$|^(ChlorContig[0-9]{1,2}(_|_x_|_s_)at)$|^(((MitoContig|Contig)[0-9]{1,6})(_|_x_|_s_)at)$|^(D[0-9]{5}_at)$|^(Dhn[0-9]{2}\(Morex\)(_|_s_)at)$|^(E(Ban|Bca|Bed|Bem|Bes|Bma|Bpi|Bro)[0-9]{2}_SQ[0-9]{3}_[A-Z]{1}[0-9]{2}(_|_s_|_x_)at)$|^(Franka(_|_b_)3pri[0-9]{1,2}(_|_s_|_x_)at)$|^(H[A-Z]{1}[0-9]{1-4}[A-Z]{1}[0-9]{1,2}[a-z]{1}(_|_x_|_s_)at)$|^(HVSME[a-z]{1}[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f)(_|_x_|_s_)at)$|^(HV_CEa[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f)(_|_x_|_s_)at)$|^(H[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{2}r(_|_x_|_s_)at)$|^(Mla([0-9]{1,2}|[0-9]{1,2}DH)(_orf_|_div5_|_5pri_|_5pri-|_consrvd_|_3pri12_)(3pri12|3pr|UTR_intron2|UTR_intron1|5pri_end)(_|_x_|_s_)at)$|^((Mla|Mlk)(_div5|_3pri12)(_|_x_|_s__at))$|^(S[0-9]{10}[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{1}(_|_x_|_s_)at)$|^((b|rb)(aak|aal|ags|ah|asd)[0-9]{1,2}[a-z]{1}[0-9]{2}(_|_x_|_s_)at)$|^(([0-9]{4,7})_(Reg|R)_([0-9]{2,4})-([0-9]{4}))$|^([0-9]{4,5}\.AF[0-9]{5})$|^(A[0-9]{5}\.[0-9]{1})$|^([A-Z]{2}[0-9]{6}|[A-Z]{2}[0-9]{6}\.1)$|^(AFFX-(BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX))$|^(AFFX-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre))$|^(ChlorContig[0-9]{1,2})$|^((MitoContig|Contig)[0-9]{1,6})$|^(D[0-9]{5})$|^(Dhn[0-9]{2}\(Morex\))$|^(E(Ban|Bca|Bed|Bem|Bes|Bma|Bpi|Bro)[0-9]{2}_SQ[0-9]{3}_[A-Z]{1}[0-9]{2})$|^(Franka(_|_b_)3pri[0-9]{1,2})$|^(H[A-Z]{1}[0-9]{1-4}[A-Z]{1}[0-9]{1,2}[a-z]{1})$|^(HVSME[a-z]{1}[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f))$|^(HV_CEa[0-9]{4}[A-Z]{1}[0-9]{2}(r2|f))$|^(H[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{2}r)$|^(Mla([0-9]{1,2}|[0-9]{1,2}DH)(_orf_|_div5_|_5pri_|_5pri-|_consrvd_|_3pri12_)(3pri12|3pr|UTR_intron2|UTR_intron1|5pri_end))$|^((Mla|Mlk)(_div5|_3pri12))$|^(S[0-9]{10}[A-Z]{1}[0-9]{2}[A-Z]{1}[0-9]{1})$|^((b|rb)(aak|aal|ags|ah|asd)[0-9]{1,2}[a-z]{1}[0-9]{2})$|^(HO)$|^(MLOC\.[0-9]{4,6}\.[0-9]{1,2})$|^(AK[0-9]{6}\.1)$|^(AJ[0-9]{6}\.1)$" +efpconfig,".{0,16}" +efpmedicago,"^(Medtr\d{1}g\d{6})$|^(Medtr\d{1}g\d{6}\.[0-9]{1})$|^(Mtr.\d{4,5}.1.[S1|S1_x|s1|s1_x]_at)$|^(AFFX-[Bio|Cre|Dap|Lys|Phe|Thr|Trpn][B|C|Dn|X]-[3|5|M]_at)$|^(AFFX-[Msa|Mtr]-[actin|gapc|gsta|ubq11|TrpnX]-[3|5|M]_[at|x_at|s_at])$|^(AFFX-Mtr|AFFX-r2-[Bs|Ec|P1]-[cre|dap|lys|phe|thr|bioB|bioC|bioD]-[3|5|M]_[at|s_at|x_at])$|^(AFFX-Mtr-ubq11-[3|5|M]_[at|s_at|x_at])$|^(AFFX-r2-Tag[A-Z]{1,2}_at|-3_at|-5_at|-M_at)$|^(Medtr_v1_\d{6})$" +efppop,"^(Ptp(Affx)?\.\d{1,6}\.\d{1,6}\.(A1|A2|S1|S2)_(x_at|s_at|at|a_at))$|^((eugene3)\.e{6,12})$|^((estExt_)(Genewise|fgenesh)(1|4)\_(v1|kg|pg|pm)(\.|\_v1\.)C_LG_\w{6,10})$|^((grail3.)\d{8,12})$|^((fgenesh)(1|4)\_(kg|pg|pm)\.C\_(scaffold|LG)\_\w{7,12})$|^((gw1)\.\w{1,6}\.\w{1,4}\.1)$|^((POPTR)\_[0-9]{4}s[0-9]{5}\.*[1-5]{0,1})$|^(Potri\.[0-9]{3}G[0-9]{6}\.[0-9]{1})$" +efprice,"^(LOC_Os[0-9]{2}g[0-9]{5})$|^((AFFX|AFFX-Os)(-|_)(Ubiquitin|Actin|Cyph|Gapdh|BioB|BioC|BioDn|CreX|DapX|LysX|PheX|ThrX|TrpnX|ef1a|gapdh)(-|_)(3|5|M)_(at|x_at|s_at))$|^(AFFX-OS-(18SrRNA|25SrRNA|5.8SrRNA)_(s_at|at))$|^((AFFX-Mgr-(actin|ef1a|gapdh)-(3|5|M))_(at|x_at|s_at))$|^(AFFX-r2-Tag(A|B|C|D|E|F|G|H)_at)$|^(AFFX-r2-Tag(IN|I|J|O|Q)-(3|5|M)_at)$|^((AFFX|AFFX-Os)-r2-(Bs|Ec|P1)-(dap|lys|phe|thr|bioB|bioC|bioD|cre)-(3|5|M)(_|_x_|_s_)at)$|^((Os|OsAffx)\.[0-9]{1,5}\.[0-9]{1}\.(S1|A1|S2)_(at|x_at|s_at|a_at))$" +efpsoybean,"^((Glyma\d{1,3}g\d{1,6}\.?\d?)$|^(Glyma\.\d{1,3}g\d{1,8}))$" +maizeefp,"^(AC[0-9]{6}\.[0-9]{1}_FG[0-9]{3})$|^(AC[0-9]{6}\.[0-9]{1}_FGT[0-9]{3})$|^(GRMZM(2|5)G[0-9]{6})$|^(GRMZM(2|5)G[0-9]{6}_T[0-9]{2})$|^(Zm\d+d\d+)$|^(Zm\d{1,10}eb\d{1,10})$" +mouse_efp,"^(XM_\d{0,8}\.\d{0,3})$|^(\d{1,10}\D\d{0,4}\D{0,4})$|^(\D{1,8}\d{0,8}\D{0,8})$|^(ENSMUSG\d{1,15})$|^(NM_\d{0,12}\d.\d{0,3})$" \ No newline at end of file diff --git a/proj_id_view_mapping.json b/proj_id_view_mapping.json new file mode 100644 index 0000000..2ec45e7 --- /dev/null +++ b/proj_id_view_mapping.json @@ -0,0 +1,1025 @@ +{ + "atgenexp_hormone": { + "classification": "partial_overlap", + "views": { + "Chemical": { + "n_view_samples": 55, + "n_matched_in_real_data_sample": 11, + "proj_ids": [ + "0", + "185", + "187", + "190", + "192" + ] + }, + "Hormone": { + "n_view_samples": 131, + "n_matched_in_real_data_sample": 14, + "proj_ids": [ + "0", + "172", + "176", + "177", + "178", + "179", + "181", + "183", + "184" + ] + } + } + }, + "atgenexp_pathogen": { + "classification": "multi_project", + "views": { + "Biotic Stress II": { + "n_view_samples": 36, + "n_matched_in_real_data_sample": 7, + "proj_ids": [ + "GEO:GSE15680", + "GEO:GSE22274", + "GEO:GSE6823" + ] + }, + "Biotic Stress": { + "n_view_samples": 195, + "n_matched_in_real_data_sample": 21, + "proj_ids": [ + "120", + "122", + "123", + "167", + "168", + "169" + ] + }, + "Biotic Stress Botrytis cinerea": { + "n_view_samples": 12, + "n_matched_in_real_data_sample": 2, + "proj_ids": [ + "167" + ] + }, + "Biotic Stress Myzus persicaere": { + "n_view_samples": 5, + "n_matched_in_real_data_sample": 1, + "proj_ids": [ + "GEO:GSE6823" + ] + }, + "Biotic Stress Elicitors": { + "n_view_samples": 42, + "n_matched_in_real_data_sample": 6, + "proj_ids": [ + "122" + ] + }, + "Biotic Stress Erysiphe orontii": { + "n_view_samples": 48, + "n_matched_in_real_data_sample": 4, + "proj_ids": [ + "169" + ] + }, + "Biotic Stress Hyaloperonospora arabidopsidis": { + "n_view_samples": 19, + "n_matched_in_real_data_sample": 5, + "proj_ids": [ + "GEO:GSE22274" + ] + }, + "Biotic Stress Phytophthora infestans": { + "n_view_samples": 18, + "n_matched_in_real_data_sample": 2, + "proj_ids": [ + "123" + ] + }, + "Biotic Stress Pseudomonas syringae": { + "n_view_samples": 75, + "n_matched_in_real_data_sample": 7, + "proj_ids": [ + "120", + "168" + ] + }, + "Biotic Stress Golovinomyces orontii": { + "n_view_samples": 12, + "n_matched_in_real_data_sample": 1, + "proj_ids": [ + "GEO:GSE15680" + ] + } + } + }, + "atgenexp_plus": { + "classification": "multi_project", + "views": { + "Developmental Mutants": { + "n_view_samples": 124, + "n_matched_in_real_data_sample": 4, + "proj_ids": [ + "GEO:GSE30547", + "GEO:GSE47632" + ] + }, + "Developmental Map": { + "n_view_samples": 140, + "n_matched_in_real_data_sample": 6, + "proj_ids": [ + "1" + ] + }, + "Tissue Specific": { + "n_view_samples": 4, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + }, + "Tissue Specific Microgametogenesis": { + "n_view_samples": 8, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + }, + "Tissue Specific Embryo Development": { + "n_view_samples": 28, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + }, + "Tissue Specific Guard And Mesophyll Cells": { + "n_view_samples": 8, + "n_matched_in_real_data_sample": 1, + "proj_ids": [ + "PID:18284694" + ] + }, + "Tissue Specific Pollen Germination": { + "n_view_samples": 15, + "n_matched_in_real_data_sample": 2, + "proj_ids": [ + "GEO:GSE17343" + ] + }, + "Tissue Specific Stem Epidermis": { + "n_view_samples": 9, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + }, + "Tissue Specific Trichomes": { + "n_view_samples": 18, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + }, + "Tissue Specific Stigma And Ovaries": { + "n_view_samples": 8, + "n_matched_in_real_data_sample": 1, + "proj_ids": [ + "GEO:GSE3056" + ] + }, + "Tissue Specific Shoot Apical Meristem": { + "n_view_samples": 9, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + }, + "Tissue Specific Xylem And Cork": { + "n_view_samples": 37, + "n_matched_in_real_data_sample": 4, + "proj_ids": [ + "92" + ] + }, + "AtGenExpress": { + "n_view_samples": 140, + "n_matched_in_real_data_sample": 6, + "proj_ids": [ + "1" + ] + } + } + }, + "atgenexp_stress": { + "classification": "multi_project", + "views": { + "Abiotic Stress II": { + "n_view_samples": 38, + "n_matched_in_real_data_sample": 5, + "proj_ids": [ + "GEO:GSE15680", + "GEO:GSE19700" + ] + }, + "Abiotic Stress": { + "n_view_samples": 272, + "n_matched_in_real_data_sample": 21, + "proj_ids": [ + "0", + "1", + "2", + "3", + "4", + "5", + "6", + "7", + "8", + "9" + ] + } + } + }, + "barley_spike_meristem": { + "classification": "duplicate_view_names", + "views": { + "Spike Meristem": { + "n_view_samples": 138, + "n_matched_in_real_data_sample": 18, + "proj_ids": [ + "1" + ] + }, + "Spike Meristem Shade Response": { + "n_view_samples": 147, + "n_matched_in_real_data_sample": 16, + "proj_ids": [ + "1" + ] + } + } + }, + "barley_spike_meristem_v3": { + "classification": "duplicate_view_names", + "views": { + "Spike Meristem Shade Response": { + "n_view_samples": 143, + "n_matched_in_real_data_sample": 16, + "proj_ids": [ + "1" + ] + }, + "Spike Meristem": { + "n_view_samples": 134, + "n_matched_in_real_data_sample": 17, + "proj_ids": [ + "1" + ] + } + } + }, + "camelina": { + "classification": "duplicate_view_names", + "views": { + "Developmental Atlas FPKM": { + "n_view_samples": 37, + "n_matched_in_real_data_sample": 17, + "proj_ids": [ + "1" + ] + }, + "Plant": { + "n_view_samples": 37, + "n_matched_in_real_data_sample": 17, + "proj_ids": [ + "1" + ] + } + } + }, + "cannabis": { + "classification": "duplicate_view_names", + "views": { + "Cannabis Atlas": { + "n_view_samples": 7, + "n_matched_in_real_data_sample": 7, + "proj_ids": [ + "1" + ] + }, + "Plant": { + "n_view_samples": 7, + "n_matched_in_real_data_sample": 7, + "proj_ids": [ + "1" + ] + } + } + }, + "eucalyptus": { + "classification": "duplicate_view_names", + "views": { + "Stress": { + "n_view_samples": 105, + "n_matched_in_real_data_sample": 13, + "proj_ids": [ + "1" + ] + }, + "Plant": { + "n_view_samples": 90, + "n_matched_in_real_data_sample": 16, + "proj_ids": [ + "1" + ] + } + } + }, + "guard_cell": { + "classification": "multi_project", + "views": { + "Guard Cell": { + "n_view_samples": 96, + "n_matched_in_real_data_sample": 26, + "proj_ids": [ + "1", + "2", + "GEO:GSE29814", + "GEO:GSE58855", + "PID:18284694" + ] + }, + "Guard Cell Meristemoids": { + "n_view_samples": 12, + "n_matched_in_real_data_sample": 5, + "proj_ids": [ + "GEO:GSE29814" + ] + }, + "Guard Cell Mutant And Wild Type Guard Cell ABA Response": { + "n_view_samples": 48, + "n_matched_in_real_data_sample": 13, + "proj_ids": [ + "1" + ] + }, + "Guard Cell Suspension Cell ABA Response With ROS Scavenger": { + "n_view_samples": 12, + "n_matched_in_real_data_sample": 1, + "proj_ids": [ + "2" + ] + } + } + }, + "human_developmental": { + "classification": "insufficient_data", + "views": { + "Circulatory Respiratory": { + "n_view_samples": 0, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + }, + "Nervous": { + "n_view_samples": 0, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + }, + "Reproductive": { + "n_view_samples": 0, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + }, + "Skeletal Immune Digestive": { + "n_view_samples": 0, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + } + } + }, + "klepikova": { + "classification": "duplicate_view_names", + "views": { + "Klepikova Atlas": { + "n_view_samples": 139, + "n_matched_in_real_data_sample": 24, + "proj_ids": [ + "1" + ] + }, + "Klepikova": { + "n_view_samples": 139, + "n_matched_in_real_data_sample": 24, + "proj_ids": [ + "1" + ] + } + } + }, + "maize_RMA_linear": { + "classification": "duplicate_view_names", + "views": { + "Sekhon et al Atlas": { + "n_view_samples": 181, + "n_matched_in_real_data_sample": 27, + "proj_ids": [ + "1" + ] + }, + "Sekhon Atlas": { + "n_view_samples": 181, + "n_matched_in_real_data_sample": 27, + "proj_ids": [ + "1" + ] + } + } + }, + "maize_buell_lab": { + "classification": "duplicate_view_names", + "views": { + "Hoopes et al Stress": { + "n_view_samples": 52, + "n_matched_in_real_data_sample": 4, + "proj_ids": [ + "1" + ] + }, + "Hoopes et al Atlas": { + "n_view_samples": 222, + "n_matched_in_real_data_sample": 24, + "proj_ids": [ + "1" + ] + } + } + }, + "maize_early_seed": { + "classification": "multi_project", + "views": { + "Early Seed": { + "n_view_samples": 32, + "n_matched_in_real_data_sample": 10, + "proj_ids": [ + "1" + ] + }, + "Maize Kernel": { + "n_view_samples": 25, + "n_matched_in_real_data_sample": 12, + "proj_ids": [ + "2" + ] + } + } + }, + "maize_ears": { + "classification": "duplicate_view_names", + "views": { + "Tassel and Ear Primordia": { + "n_view_samples": 8, + "n_matched_in_real_data_sample": 8, + "proj_ids": [ + "1" + ] + }, + "Tassel And Ear Primordia": { + "n_view_samples": 8, + "n_matched_in_real_data_sample": 8, + "proj_ids": [ + "1" + ] + } + } + }, + "maize_gdowns": { + "classification": "duplicate_view_names", + "views": { + "Downs et al Atlas": { + "n_view_samples": 151, + "n_matched_in_real_data_sample": 29, + "proj_ids": [ + "GD01" + ] + }, + "Plant": { + "n_view_samples": 151, + "n_matched_in_real_data_sample": 29, + "proj_ids": [ + "GD01" + ] + } + } + }, + "maize_iplant": { + "classification": "duplicate_view_names", + "views": { + "maize iplant": { + "n_view_samples": 7, + "n_matched_in_real_data_sample": 7, + "proj_ids": [ + "1", + "2" + ] + }, + "Leaf MeBS": { + "n_view_samples": 7, + "n_matched_in_real_data_sample": 7, + "proj_ids": [ + "1", + "2" + ] + } + } + }, + "maize_leaf_gradient": { + "classification": "duplicate_view_names", + "views": { + "maize leaf gradient": { + "n_view_samples": 16, + "n_matched_in_real_data_sample": 16, + "proj_ids": [ + "1" + ] + }, + "Leaf Gradient": { + "n_view_samples": 16, + "n_matched_in_real_data_sample": 16, + "proj_ids": [ + "1" + ] + } + } + }, + "maize_root": { + "classification": "duplicate_view_names", + "views": { + "Maize Root": { + "n_view_samples": 16, + "n_matched_in_real_data_sample": 14, + "proj_ids": [ + "1" + ] + }, + "Root": { + "n_view_samples": 16, + "n_matched_in_real_data_sample": 14, + "proj_ids": [ + "1" + ] + } + } + }, + "medicago_mas": { + "classification": "duplicate_view_names", + "views": { + "medicago mas": { + "n_view_samples": 55, + "n_matched_in_real_data_sample": 24, + "proj_ids": [ + "1" + ] + }, + "Plant": { + "n_view_samples": 55, + "n_matched_in_real_data_sample": 24, + "proj_ids": [ + "1" + ] + } + } + }, + "medicago_root": { + "classification": "duplicate_view_names", + "views": { + "Root": { + "n_view_samples": 31, + "n_matched_in_real_data_sample": 4, + "proj_ids": [ + "1" + ] + }, + "Root Component": { + "n_view_samples": 81, + "n_matched_in_real_data_sample": 13, + "proj_ids": [ + "1" + ] + } + } + }, + "medicago_seed": { + "classification": "duplicate_view_names", + "views": { + "medicago seed": { + "n_view_samples": 52, + "n_matched_in_real_data_sample": 22, + "proj_ids": [ + "1" + ] + }, + "Seed": { + "n_view_samples": 52, + "n_matched_in_real_data_sample": 22, + "proj_ids": [ + "1" + ] + } + } + }, + "poplar": { + "classification": "multi_project", + "views": { + "Poplar": { + "n_view_samples": 26, + "n_matched_in_real_data_sample": 10, + "proj_ids": [ + "GEO:GSE13990" + ] + }, + "PoplarTreatment": { + "n_view_samples": 48, + "n_matched_in_real_data_sample": 12, + "proj_ids": [ + "GEO:GSE15242" + ] + }, + "Plant": { + "n_view_samples": 26, + "n_matched_in_real_data_sample": 10, + "proj_ids": [ + "GEO:GSE13990" + ] + }, + "Poplar Treatment": { + "n_view_samples": 48, + "n_matched_in_real_data_sample": 12, + "proj_ids": [ + "GEO:GSE15242" + ] + } + } + }, + "potato_dev": { + "classification": "duplicate_view_names", + "views": { + "Potato Developmental": { + "n_view_samples": 32, + "n_matched_in_real_data_sample": 18, + "proj_ids": [ + "1" + ] + }, + "Plant": { + "n_view_samples": 32, + "n_matched_in_real_data_sample": 18, + "proj_ids": [ + "1" + ] + } + } + }, + "rice_leaf_gradient": { + "classification": "duplicate_view_names", + "views": { + "rice leaf gradient": { + "n_view_samples": 12, + "n_matched_in_real_data_sample": 12, + "proj_ids": [ + "1" + ] + }, + "Leaf Gradient": { + "n_view_samples": 12, + "n_matched_in_real_data_sample": 12, + "proj_ids": [ + "1" + ] + } + } + }, + "rice_mas": { + "classification": "multi_project", + "views": { + "rice mas": { + "n_view_samples": 46, + "n_matched_in_real_data_sample": 14, + "proj_ids": [ + "1", + "2", + "3" + ] + }, + "riceanoxia mas": { + "n_view_samples": 5, + "n_matched_in_real_data_sample": 2, + "proj_ids": [ + "2", + "3" + ] + }, + "ricestress mas": { + "n_view_samples": 10, + "n_matched_in_real_data_sample": 2, + "proj_ids": [ + "4" + ] + }, + "ricestigma mas": { + "n_view_samples": 14, + "n_matched_in_real_data_sample": 7, + "proj_ids": [ + "2", + "3" + ] + }, + "Anoxia": { + "n_view_samples": 5, + "n_matched_in_real_data_sample": 2, + "proj_ids": [ + "2", + "3" + ] + }, + "Stigma": { + "n_view_samples": 14, + "n_matched_in_real_data_sample": 7, + "proj_ids": [ + "2", + "3" + ] + }, + "Stress": { + "n_view_samples": 10, + "n_matched_in_real_data_sample": 2, + "proj_ids": [ + "4" + ] + }, + "Plant": { + "n_view_samples": 46, + "n_matched_in_real_data_sample": 14, + "proj_ids": [ + "1", + "2", + "3" + ] + } + } + }, + "rice_rma": { + "classification": "multi_project", + "views": { + "rice rma": { + "n_view_samples": 46, + "n_matched_in_real_data_sample": 19, + "proj_ids": [ + "1", + "2", + "3" + ] + }, + "riceanoxia rma": { + "n_view_samples": 5, + "n_matched_in_real_data_sample": 1, + "proj_ids": [ + "2", + "3" + ] + }, + "ricestigma rma": { + "n_view_samples": 14, + "n_matched_in_real_data_sample": 4, + "proj_ids": [ + "2", + "3" + ] + }, + "ricestress rma": { + "n_view_samples": 10, + "n_matched_in_real_data_sample": 2, + "proj_ids": [ + "4" + ] + } + } + }, + "root": { + "classification": "partial_overlap", + "views": { + "Root II": { + "n_view_samples": 185, + "n_matched_in_real_data_sample": 13, + "proj_ids": [ + "GEO:GSE25171", + "GEO:GSE30095", + "GEO:GSE30096", + "GEO:GSE30099", + "GEO:GSE30166", + "GEO:GSE35580", + "GEO:GSE7641" + ] + }, + "Root": { + "n_view_samples": 269, + "n_matched_in_real_data_sample": 14, + "proj_ids": [ + "1", + "GEO:GSE10576", + "GEO:GSE7631", + "GEO:GSE7639", + "GEO:GSE7641", + "GEO:GSE7642" + ] + }, + "Tissue Specific Root": { + "n_view_samples": 0, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + } + } + }, + "single_cell": { + "classification": "insufficient_data", + "views": { + "Single Cell": { + "n_view_samples": 109, + "n_matched_in_real_data_sample": 25, + "proj_ids": [ + "1" + ] + }, + "Cell Type": { + "n_view_samples": 0, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + }, + "Cell": { + "n_view_samples": 0, + "n_matched_in_real_data_sample": 0, + "proj_ids": [] + } + } + }, + "soybean": { + "classification": "duplicate_view_names", + "views": { + "soybean": { + "n_view_samples": 15, + "n_matched_in_real_data_sample": 14, + "proj_ids": [ + "1" + ] + }, + "Plant": { + "n_view_samples": 15, + "n_matched_in_real_data_sample": 14, + "proj_ids": [ + "1" + ] + } + } + }, + "soybean_severin": { + "classification": "duplicate_view_names", + "views": { + "soybean severin": { + "n_view_samples": 15, + "n_matched_in_real_data_sample": 13, + "proj_ids": [ + "1" + ] + }, + "Soybean Severin": { + "n_view_samples": 15, + "n_matched_in_real_data_sample": 13, + "proj_ids": [ + "1" + ] + } + } + }, + "strawberry": { + "classification": "duplicate_view_names", + "views": { + "Strawberry Green vs White Stage": { + "n_view_samples": 9, + "n_matched_in_real_data_sample": 1, + "proj_ids": [ + "1" + ] + }, + "Developmental Map Strawberry Flower and Fruit": { + "n_view_samples": 85, + "n_matched_in_real_data_sample": 24, + "proj_ids": [ + "1" + ] + } + } + }, + "tomato_ils": { + "classification": "duplicate_view_names", + "views": { + "ILs Leaf Chitwood et al": { + "n_view_samples": 77, + "n_matched_in_real_data_sample": 24, + "proj_ids": [ + "1" + ] + }, + "LeafILs": { + "n_view_samples": 77, + "n_matched_in_real_data_sample": 24, + "proj_ids": [ + "1" + ] + } + } + }, + "tomato_ils2": { + "classification": "duplicate_view_names", + "views": { + "ILs Root Tip Brady Lab": { + "n_view_samples": 80, + "n_matched_in_real_data_sample": 24, + "proj_ids": [ + "1" + ] + }, + "RootILs": { + "n_view_samples": 80, + "n_matched_in_real_data_sample": 24, + "proj_ids": [ + "1" + ] + } + } + }, + "tomato_renormalized": { + "classification": "multi_project", + "views": { + "Rose Lab Atlas Renormalized": { + "n_view_samples": 21, + "n_matched_in_real_data_sample": 18, + "proj_ids": [ + "1", + "2" + ] + }, + "Fruit": { + "n_view_samples": 6, + "n_matched_in_real_data_sample": 5, + "proj_ids": [ + "1" + ] + }, + "Plant": { + "n_view_samples": 15, + "n_matched_in_real_data_sample": 13, + "proj_ids": [ + "2" + ] + } + } + }, + "tomato_s_pennellii": { + "classification": "duplicate_view_names", + "views": { + "M82 S pennellii Atlases Koenig et al": { + "n_view_samples": 17, + "n_matched_in_real_data_sample": 12, + "proj_ids": [ + "1" + ] + }, + "TomatoAtlases": { + "n_view_samples": 17, + "n_matched_in_real_data_sample": 12, + "proj_ids": [ + "1" + ] + } + } + }, + "wheat": { + "classification": "duplicate_view_names", + "views": { + "Developmental Atlas": { + "n_view_samples": 209, + "n_matched_in_real_data_sample": 26, + "proj_ids": [ + "1" + ] + }, + "EarlyStages": { + "n_view_samples": 61, + "n_matched_in_real_data_sample": 9, + "proj_ids": [ + "1" + ] + }, + "MiddleStages": { + "n_view_samples": 88, + "n_matched_in_real_data_sample": 11, + "proj_ids": [ + "1" + ] + }, + "LateStages": { + "n_view_samples": 62, + "n_matched_in_real_data_sample": 6, + "proj_ids": [ + "1" + ] + } + } + } +} \ No newline at end of file diff --git a/scrape_species_view_info.py b/scrape_species_view_info.py new file mode 100644 index 0000000..7bb6138 --- /dev/null +++ b/scrape_species_view_info.py @@ -0,0 +1,273 @@ +""" +Reena Obmina | BCB330 Project 2025-2026 | University of Toronto + +Scrapes groups, controls, and treatments for every view of every species, +covering BOTH eFP databases and ePlant databases, tagged by source so +eFP-only / ePlant-only / shared databases can be told apart. + +Reuses the live site/view discovery already built and verified in +scrape_view_databases.py (same dropdown/viewNames.json + XML paths) instead +of duplicating it here. This replaces the old approach of reading +__pycache__/eplant_efp_views/eplant_audit.json (Vincent's server-local-only +ePlant audit) for ePlant layout info -- that file isn't available to other +team members and could go stale, whereas viewNames.json is live and public. +Run scrape_view_databases.py first if you only want the flat view->db +mapping (species_databases.json); this script additionally pulls each +view's full group/tissue/sample breakdown. + +Reads: {efp_base}/data/{datasource}.xml for each eFP species + {eplant_base}/data/{family}/viewNames.json + per-view XML for each ePlant project +Writes: data/efp_info/efp_eplant_species_view_info.json -- combined output, + each view tagged "source": "efp" or "eplant", keyed the same way as + species_databases.json ("efp_" / "eplant_") + data/efp_info/db_source_summary.json -- db name -> efp/eplant/both +""" + +import json +import xml.etree.ElementTree as ET +from concurrent.futures import ThreadPoolExecutor, as_completed + +import requests + +from scrape_view_databases import ( + EFP_SITES, + _SPECIAL_CASES, + _HARDCODED, + _EFP_FALLBACK, + get_datasource_options, + EPLANT_SITES, + EPLANT_SPECIES_FILE, + EPLANT_FAMILIES, + EPLANT_DB_OVERRIDE, + get_eplant_view_names, + _flat_view_label, + _NESTED_EFPS_FAMILIES, +) + +REQUEST_TIMEOUT = 20 + + +def fetch_xml_root(xml_url): + """Fetch a view's XML and return the parsed root element, or None on failure.""" + try: + resp = requests.get(xml_url, timeout=REQUEST_TIMEOUT) + resp.raise_for_status() + return ET.fromstring(resp.content) + except Exception as e: + print(f" Error fetching {xml_url}: {e}") + return None + + +def extract_db(root): + """Return the db attribute from the first element, or None.""" + view = root.find(".//view") + return view.get("db") if view is not None else None + + +def parse_groups(root): + """Parse // elements into {group_name: {controls, treatments}}.""" + groups = {} + for group in root.findall(".//group"): + group_name = group.get("name") + if not group_name: + continue + + controls = [c.get("sample") for c in group.findall("control") if c.get("sample")] + + treatments = {} + for tissue in group.findall("tissue"): + t_name = tissue.get("name") + if not t_name: + continue + t_key = t_name.replace(" ", "_") + samples = [s.get("name") for s in tissue.findall("sample") if s.get("name")] + treatments.setdefault(t_key, []) + treatments[t_key].extend(samples) + + groups[group_name.replace(" ", "_")] = {"controls": controls, "treatments": treatments} + + return groups + + +# --------------------------------------------------------------------------- +# eFP +# --------------------------------------------------------------------------- + + +def fetch_efp_view(species, base_url, value, label): + """Fetch one eFP view's XML and return its db + group breakdown, tagged as eFP.""" + xml_url = f"{base_url}/data/{value}.xml" + root = fetch_xml_root(xml_url) + if root is None: + return None + return { + "source": "efp", + "species": species, + "database": extract_db(root), + "view_name": label, + "view_file": value, + "groups": parse_groups(root), + } + + +def _hardcoded_or_fallback_views(species, db_by_label): + """Build view entries (no group data available) for a hardcoded/fallback species.""" + return [ + { + "source": "efp", + "species": species, + "database": db_name, + "view_name": label, + "view_file": None, + "groups": {}, + } + for label, db_name in db_by_label.items() + ] + + +def collect_efp_views(): + """Discover and fetch every eFP species' views.""" + results = {} + for species, efp_url in EFP_SITES.items(): + print(f"[efp] Processing {species}...") + base_url = efp_url.rsplit("/", 2)[0] + key = f"efp_{species.replace(' ', '_')}" + + if species in _HARDCODED: + results[key] = _hardcoded_or_fallback_views(species, _HARDCODED[species]) + continue + + options = _SPECIAL_CASES.get(species) or get_datasource_options(efp_url) + if not options: + if species in _EFP_FALLBACK: + print(" Live scrape failed -- using last-known-good fallback (no group data)") + results[key] = _hardcoded_or_fallback_views(species, _EFP_FALLBACK[species]) + else: + print(" No views found") + results[key] = [] + continue + + species_views = [] + with ThreadPoolExecutor(max_workers=6) as pool: + futures = { + pool.submit(fetch_efp_view, species, base_url, value, label): label + for value, label in options + } + for future in as_completed(futures): + view = future.result() + if view: + species_views.append(view) + print(f" Found {len(species_views)} views") + results[key] = species_views + return results + + +# --------------------------------------------------------------------------- +# ePlant +# --------------------------------------------------------------------------- + + +def eplant_xml_url(base_url, family, folder, species_file): + """Build the XML URL for an ePlant view, mirroring scrape_view_databases.fetch_eplant_db.""" + if folder is None: + return f"{base_url}/data/{family}/{species_file}.xml" + nested = "efps/" if family in _NESTED_EFPS_FAMILIES else "" + return f"{base_url}/data/{family}/{nested}{folder}/{species_file}.xml" + + +def fetch_eplant_view(site, base_url, family, display, folder, species_file): + """Fetch one ePlant view's XML and return its db + group breakdown, tagged as ePlant. + + The view is kept even when no db="..." attribute is present (e.g. eplant_tomato's + Cell viewer), with database: None, so view counts match Vincent's eplant_views.csv + audit exactly -- a real view with an unknown database is still a real view. + """ + xml_url = eplant_xml_url(base_url, family, folder, species_file) + root = fetch_xml_root(xml_url) + if root is None: + return None + db = extract_db(root) or EPLANT_DB_OVERRIDE.get((site, family)) + return { + "source": "eplant", + "project": site, + "species": species_file, + "family": family, + "database": db, + "view_name": display, + "view_folder": folder, + "groups": parse_groups(root), + } + + +def collect_eplant_views(): + """Discover (via viewNames.json, same as scrape_view_databases.py) and fetch every ePlant view.""" + jobs = [] + for site, base_url in EPLANT_SITES.items(): + species_file = EPLANT_SPECIES_FILE[site] + for family in EPLANT_FAMILIES[site]: + names = get_eplant_view_names(base_url, family) + if names is not None: + for display in names: + folder = display.replace(" ", "") + jobs.append((site, base_url, family, display, folder, species_file)) + else: + jobs.append((site, base_url, family, _flat_view_label(family), None, species_file)) + + results = {} + print(f"[eplant] Fetching {len(jobs)} candidate views across {len(EPLANT_SITES)} projects...") + with ThreadPoolExecutor(max_workers=6) as pool: + futures = {pool.submit(fetch_eplant_view, *job): job[0] for job in jobs} + for future in as_completed(futures): + site = futures[future] + view = future.result() + if view: + results.setdefault(site, []).append(view) + for site in EPLANT_SITES: + print(f" {site}: fetched {len(results.get(site, []))} views") + return results + + +def build_db_source_summary(efp_results, eplant_results): + """Map each database name to which source(s) it appears under.""" + summary = {} + for views in efp_results.values(): + for view in views: + db = view.get("database") + if db: + summary.setdefault(db, set()).add("efp") + for views in eplant_results.values(): + for view in views: + db = view.get("database") + if db: + summary.setdefault(db, set()).add("eplant") + + return { + db: ("both" if sources == {"efp", "eplant"} else next(iter(sources))) + for db, sources in summary.items() + } + + +def main(): + efp_results = collect_efp_views() + eplant_results = collect_eplant_views() + + combined = {"efp": efp_results, "eplant": eplant_results} + out_file = "data/efp_info/efp_eplant_species_view_info.json" + with open(out_file, "w") as f: + json.dump(combined, f, indent=2) + print(f"\nOutput written to {out_file}") + + db_summary = build_db_source_summary(efp_results, eplant_results) + summary_file = "data/efp_info/db_source_summary.json" + with open(summary_file, "w") as f: + json.dump(db_summary, f, indent=2, sort_keys=True) + print(f"Output written to {summary_file}") + + efp_only = sum(1 for v in db_summary.values() if v == "efp") + eplant_only = sum(1 for v in db_summary.values() if v == "eplant") + both = sum(1 for v in db_summary.values() if v == "both") + print(f"\nDatabases: {len(db_summary)} total -- eFP-only: {efp_only}, ePlant-only: {eplant_only}, both: {both}") + + +if __name__ == "__main__": + main() diff --git a/scrape_view_databases.py b/scrape_view_databases.py new file mode 100644 index 0000000..4cacebf --- /dev/null +++ b/scrape_view_databases.py @@ -0,0 +1,420 @@ +""" +Reena Obmina | BCB330 Project 2025-2026 | University of Toronto + +Scrapes view names and their database names from each species' datasources.xml, +covering BOTH eFP databases and ePlant databases, so the master list notes which +databases are eFP-only, ePlant-only, or available through both frontends. + +eFP side: + Reads: {efp_base}/data/{datasource}.xml for each datasource in each species' + HTML dropdown (discovered live from the efpWeb.cgi page itself). + +ePlant side: + Each ePlant project (e.g. eplant_maize) has its own set of "*eFP viewer" tabs + (family names like "experiment", "plant", "cell" -- "Tissue and experiment eFP + viewer", "Plant eFP viewer", "Cell eFP viewer"). When a tab has more than one + view, the app populates a "Select View" dropdown from {base}/data/{family}/ + viewNames.json. When a tab has exactly one view, there's no dropdown/JSON file + and the view's XML sits directly at {base}/data/{family}/{species_file}.xml. + Reads: {eplant_base}/data/{family}/viewNames.json (dropdown views, if any) + {eplant_base}/data/{family}/efps/{folder}/{species_file}.xml (per-view + XML for the "experiment" family, which nests views under "efps/") + {eplant_base}/data/{family}/{folder}/{species_file}.xml (per-view XML + for other families, which nest views directly) + The per-project species filename and family list are stable, project-specific + paths on the server and aren't otherwise discoverable over HTTP, so they're + hardcoded below (cross-checked against Vincent's eplant_audit.json). + +Writes: species_databases.json -- ``{ species_or_project: { view_name: db_name, ... }, ... }`` + Keys prefixed "efp_" + the eFP species (e.g. "efp_arabidopsis") or "eplant_" + + the ePlant project's species (e.g. "eplant_maize") so eFP-only vs ePlant-only vs shared databases + can be told apart just by which key(s) a db name shows up under. + +Run this first to discover what views exist for a species before running +build_proj_id_view_mapping.py. +""" + +import re +import xml.etree.ElementTree as ET +import json + +import requests + +# --------------------------------------------------------------------------- +# eFP sites +# --------------------------------------------------------------------------- +EFP_SITES = { + "arabidopsis": "https://bar.utoronto.ca/efp_arabidopsis/cgi-bin/efpWeb.cgi", + "arabidopsis lipid": "https://bar.utoronto.ca/efp_arabidopsis_lipid/cgi-bin/efpWeb.cgi", + "arabidopsis cell": "https://bar.utoronto.ca/cell_efp/cgi-bin/cell_efp.cgi", + "arabidopsis seedcoat": "https://bar.utoronto.ca/efp_seedcoat/cgi-bin/efpWeb.cgi", + "poplar": "https://bar.utoronto.ca/efppop/cgi-bin/efpWeb.cgi", + "medicago": "https://bar.utoronto.ca/efpmedicago/cgi-bin/efpWeb.cgi", + "soybean": "https://bar.utoronto.ca/efpsoybean/cgi-bin/efpWeb.cgi", + "potato": "https://bar.utoronto.ca/efp_potato/cgi-bin/efpWeb.cgi", + "tomato": "https://bar.utoronto.ca/efp_tomato/cgi-bin/efpWeb.cgi", + "eutrema": "https://bar.utoronto.ca/efp_eutrema/cgi-bin/efpWeb.cgi", + "camelina": "https://bar.utoronto.ca/efp_camelina/cgi-bin/efpWeb.cgi", + "arachis": "https://bar.utoronto.ca/efp_arachis/cgi-bin/efpWeb.cgi", + "grape": "https://bar.utoronto.ca/efp_grape/cgi-bin/efpWeb.cgi", + "cannabis": "https://bar.utoronto.ca/efp_cannabis/cgi-bin/efpWeb.cgi", + "kalanchoe": "https://bar.utoronto.ca/efp_kalanchoe/cgi-bin/efpWeb.cgi", + "actinidia": "https://bar.utoronto.ca/efp_actinidia/cgi-bin/efpWeb.cgi", + "brassica rapa": "https://bar.utoronto.ca/efp_brassica_rapa/cgi-bin/efpWeb.cgi", + "canola": "https://bar.utoronto.ca/efp_canola/cgi-bin/efpWeb.cgi", + "cacao ccn": "https://bar.utoronto.ca/efp_cacao_ccn/cgi-bin/efpWeb.cgi", + "cacao sca": "https://bar.utoronto.ca/efp_cacao_sca/cgi-bin/efpWeb.cgi", + "cacao tc": "https://bar.utoronto.ca/efp_cacao_tc/cgi-bin/efpWeb.cgi", + "mangosteen": "https://bar.utoronto.ca/efp_mangosteen/cgi-bin/efpWeb.cgi", + "lupin": "https://bar.utoronto.ca/efp_lupin/cgi-bin/efpWeb.cgi", + "strawberry": "https://bar.utoronto.ca/efp_strawberry/cgi-bin/efpWeb.cgi", + "maize": "https://bar.utoronto.ca/efp_maize/cgi-bin/efpWeb.cgi", + "rice": "https://bar.utoronto.ca/efprice/cgi-bin/efpWeb.cgi", + "barley": "https://bar.utoronto.ca/efpbarley/cgi-bin/efpWeb.cgi", + "triticale": "https://bar.utoronto.ca/efp_triticale/cgi-bin/efpWeb.cgi", + "brachypodium": "https://bar.utoronto.ca/efp_brachypodium/cgi-bin/efpWeb.cgi", + "wheat": "https://bar.utoronto.ca/efp_wheat/cgi-bin/efpWeb.cgi", + "little millet": "https://bar.utoronto.ca/efp_little_millet/cgi-bin/efpWeb.cgi", + "oat": "https://bar.utoronto.ca/efp_oat/cgi-bin/efpWeb.cgi", + "physcomitrella": "https://bar.utoronto.ca/efp_physcomitrella/cgi-bin/efpWeb.cgi", + "selaginella": "https://bar.utoronto.ca/efp_selaginella/cgi-bin/efpWeb.cgi", + "mouse": "https://bar.utoronto.ca/mouse_efp/cgi-bin/efpWeb.cgi", + "human": "https://bar.utoronto.ca/efp_human/cgi-bin/efpWeb.cgi", + "phelipanche": "https://bar.utoronto.ca/efp_phelipanche/cgi-bin/efpWeb.cgi", + "striga": "https://bar.utoronto.ca/efp_striga/cgi-bin/efpWeb.cgi", + "triphysaria": "https://bar.utoronto.ca/efp_triphysaria/cgi-bin/efpWeb.cgi", + # Found by cross-checking api/random_rows_json/ sample data against this site + # list: these sites exist live but were never added here. + "durum wheat": "https://bar.utoronto.ca/efp_durum_wheat/cgi-bin/efpWeb.cgi", + "euphorbia": "https://bar.utoronto.ca/efp_euphorbia/cgi-bin/efpWeb.cgi", + "marchantia": "https://bar.utoronto.ca/efp_marchantia/cgi-bin/efpWeb.cgi", + "sorghum": "https://bar.utoronto.ca/efp_sorghum/cgi-bin/efpWeb.cgi", + "tung tree": "https://bar.utoronto.ca/efp_tung_tree/cgi-bin/efpWeb.cgi", + "apple": "https://bar.utoronto.ca/efp_apple/cgi-bin/efpWeb.cgi", + # Metabolite/enzyme-class sites -- see _HARDCODED below for why these are + # single fixed views rather than scraped dropdowns. + "maize enzyme": "https://bar.utoronto.ca/efp_maize_enzyme/cgi-bin/efpWeb.cgi", + "maize metabolite": "https://bar.utoronto.ca/efp_maize_metabolite/cgi-bin/efpWeb.cgi", + "rice metabolite": "https://bar.utoronto.ca/efp_rice_metabolite/cgi-bin/efpWeb.cgi", + "brachypodium metabolites": "https://bar.utoronto.ca/efp_brachypodium_metabolites/cgi-bin/efpWeb.cgi", +} + +# Sites that do not use the standard dataSource dropdown; map them manually. +# (species key → list of (datasource_xml_filename, display_name) to look up) +_SPECIAL_CASES = { + # Uses a lipidClass dropdown instead of dataSource; one fixed XML file. + "arabidopsis lipid": [("Lipid_Map", "Lipid Map")], +} + +# Sites with no discoverable XML; database names are hardcoded from known config. +_HARDCODED = { + # Single-view cell browser with no dropdown and access-denied data directory. + "arabidopsis cell": {"Cell Type": "single_cell"}, + # Metabolite/enzyme-class eFPs: the dataSource dropdown lists individual + # compounds/enzymes (e.g. "Rubisco (initial)", "Glucose-6-phosphate") as the + # *query parameter* into one single database, not separate per-compound + # databases -- their XML has no per-option db= attribute. Confirmed against + # Vincent's regex patterns (efp_maize_enzyme etc. validate the compound NAME + # as the "gene_id", not a real gene ID) and the one underlying db each site + # actually has sample data for. + "maize enzyme": {"Enzyme Activity": "maize_enzyme"}, + "maize metabolite": {"Metabolite Level": "maize_metabolite"}, + "rice metabolite": {"Metabolite Level": "rice_metabolite"}, + "brachypodium metabolites": {"Metabolite Level": "brachypodium_metabolites_map"}, +} + +# efp_human currently 403s for us (server-side block, not a code issue). Fall back +# to the last-known-good scrape rather than silently dropping "human" from the output. +_EFP_FALLBACK = { + "human": { + "Circulatory Respiratory": "human_developmental", + "Illumina Body Map 2 - FPKM": "human_body_map_2", + "Nervous": "human_developmental", + "Reproductive": "human_developmental", + "Skeletal Immune Digestive": "human_developmental", + }, +} + +# --------------------------------------------------------------------------- +# ePlant sites +# --------------------------------------------------------------------------- +EPLANT_SITES = { + "eplant_arabidopsis": "https://bar.utoronto.ca/eplant", + "eplant_maize": "https://bar.utoronto.ca/eplant_maize", + "eplant_poplar": "https://bar.utoronto.ca/eplant_poplar", + "eplant_tomato": "https://bar.utoronto.ca/eplant_tomato", + "eplant_camelina": "https://bar.utoronto.ca/eplant_camelina", + "eplant_soybean": "https://bar.utoronto.ca/eplant_soybean", + "eplant_potato": "https://bar.utoronto.ca/eplant_potato", + "eplant_barley": "https://bar.utoronto.ca/eplant_barley", + "eplant_barley_legacy": "https://bar.utoronto.ca/eplant_barley_legacy", + "eplant_medicago": "https://bar.utoronto.ca/eplant_medicago", + "eplant_eucalyptus": "https://bar.utoronto.ca/eplant_eucalyptus", + "eplant_rice": "https://bar.utoronto.ca/eplant_rice", + "eplant_willow": "https://bar.utoronto.ca/eplant_willow", + "eplant_sunflower": "https://bar.utoronto.ca/eplant_sunflower", + "eplant_cannabis": "https://bar.utoronto.ca/eplant_cannabis", + "eplant_wheat": "https://bar.utoronto.ca/eplant_wheat", + "eplant_sugarcane": "https://bar.utoronto.ca/eplant_sugarcane", +} + +# Species filename used in each ePlant project's per-view XML paths +# (e.g. .../data/experiment/efps/AbioticStress/Arabidopsis_thaliana.xml). +# Sourced from Vincent's eplant_audit.json (species detection per project); +# not discoverable over HTTP since these sites don't expose species.json publicly. +EPLANT_SPECIES_FILE = { + "eplant_arabidopsis": "Arabidopsis_thaliana", + "eplant_maize": "Zea_mays", + "eplant_poplar": "Populus_trichocarpa", + "eplant_tomato": "Solanum_lycopersicum", + "eplant_camelina": "Camelina_sativa", + "eplant_soybean": "Glycine_max", + "eplant_potato": "Solanum_tuberosum", + "eplant_barley": "Hordeum_vulgare", + "eplant_barley_legacy": "Hordeum_vulgare", + "eplant_medicago": "Medicago_truncatula", + "eplant_eucalyptus": "Eucalyptus_grandis", + "eplant_rice": "Oryza_sativa", + "eplant_willow": "Salix_purpurea", + "eplant_sunflower": "Helianthus_annuus", + "eplant_cannabis": "Cannabis_sativa", + "eplant_wheat": "Triticum_aestivum", + "eplant_sugarcane": "Saccharum_R570", +} + +# "*eFP viewer" tabs (families) every ePlant project has, plus per-project extras. +_DEFAULT_EPLANT_FAMILIES = ["cell", "experiment", "plant"] +EPLANT_FAMILIES = { + site: (["cell", "experiment", "plant", "worldLeaf", "worldXylem"] if site == "eplant_poplar" else _DEFAULT_EPLANT_FAMILIES) + for site in EPLANT_SITES +} + +# Families always nest their per-view XML under an "efps/" subfolder. +_NESTED_EFPS_FAMILIES = {"experiment"} + +# Views whose XML has no db="..." attribute to scrape (single-cell browsers); +# the db is known from existing eFP config instead. +EPLANT_DB_OVERRIDE = { + ("eplant_arabidopsis", "cell"): "single_cell", +} + + +def get_datasource_options(efp_url): + """Fetch the eFP HTML page and extract all datasource option values and display names. + + :param efp_url: Full URL to the species' eFP CGI endpoint. + :type efp_url: str + :returns: List of (option_value, display_name) tuples, or empty list on failure. + :rtype: list[tuple[str, str]] + """ + options = [] + try: + resp = requests.get(efp_url, timeout=15) + resp.raise_for_status() + html = resp.text + + # Match + pattern = re.compile( + r']*>\s*([^<]+?)\s*', + re.IGNORECASE | re.DOTALL, + ) + for match in pattern.finditer(html): + value = match.group(1).strip() + label = match.group(2).strip() + if value and label: + options.append((value, label)) + except Exception as e: + print(f" Error fetching HTML: {e}") + return options + + +def fetch_db_name(base_url, datasource_value): + """Fetch the per-datasource XML and return the first database name found. + + :param base_url: Base URL for the eFP site (e.g. ``'https://bar.utoronto.ca/efp_arabidopsis'``). + :type base_url: str + :param datasource_value: Option value from the dropdown (e.g. ``'Developmental_Map'``). + :type datasource_value: str + :returns: Database name string, or ``None`` if not found. + :rtype: str | None + """ + xml_url = f"{base_url}/data/{datasource_value}.xml" + try: + resp = requests.get(xml_url, timeout=15) + resp.raise_for_status() + root = ET.fromstring(resp.content) + view = root.find(".//view") + if view is not None: + return view.get("db") + except Exception: + pass + return None + + +def fetch_view_databases(species, efp_url): + """Fetch view name → database name mappings for one eFP species. + + :param species: Species key (e.g. ``'arabidopsis'``), used only for error messages. + :type species: str + :param efp_url: Full URL to the species' efpWeb.cgi endpoint. + :type efp_url: str + :returns: Dict mapping view display name to database name, or an empty dict on failure. + :rtype: dict[str, str] + """ + base_url = efp_url.rsplit("/", 2)[0] + + if species in _HARDCODED: + return _HARDCODED[species] + + if species in _SPECIAL_CASES: + options = _SPECIAL_CASES[species] + else: + options = get_datasource_options(efp_url) + if not options: + return {} + + views = {} + for value, label in options: + db_name = fetch_db_name(base_url, value) + if db_name: + views[label] = db_name + else: + print(f" No db found for datasource '{value}' ({label})") + + return views + + +def get_eplant_view_names(base_url, family): + """Fetch the "Select View" dropdown options for one ePlant family, if any. + + :param base_url: Base URL for the ePlant project (e.g. ``'https://bar.utoronto.ca/eplant_maize'``). + :type base_url: str + :param family: Family/tab name (e.g. ``'experiment'``, ``'plant'``, ``'cell'``). + :type family: str + :returns: List of display names (possibly empty) if a dropdown exists, else ``None`` + when there's no viewNames.json at all (single-view or no-view family). + :rtype: list[str] | None + """ + url = f"{base_url}/data/{family}/viewNames.json" + try: + resp = requests.get(url, timeout=15) + resp.raise_for_status() + names = resp.json() + if isinstance(names, list): + return [n.strip() for n in names if isinstance(n, str) and n.strip()] + except Exception: + pass + return None + + +def fetch_eplant_db(base_url, family, folder, species_file): + """Fetch one ePlant view's XML and return its db attribute. + + :param base_url: Base URL for the ePlant project. + :type base_url: str + :param family: Family/tab name the view belongs to. + :type family: str + :param folder: View's on-disk folder name (display name with spaces removed), or + ``None`` for a flat family with no per-view subfolder (XML sits directly under + the family directory). + :type folder: str | None + :param species_file: Species XML filename stem (e.g. ``'Zea_mays'``). + :type species_file: str + :returns: Database name string, or ``None`` if not found. + :rtype: str | None + """ + if folder is None: + xml_url = f"{base_url}/data/{family}/{species_file}.xml" + else: + nested = "efps/" if family in _NESTED_EFPS_FAMILIES else "" + xml_url = f"{base_url}/data/{family}/{nested}{folder}/{species_file}.xml" + try: + resp = requests.get(xml_url, timeout=15) + resp.raise_for_status() + root = ET.fromstring(resp.content) + view = root.find(".//view") + if view is not None: + return view.get("db") + except Exception: + pass + return None + + +def _flat_view_label(family): + """Turn a single-view family name into a display label, e.g. 'worldLeaf' -> 'World Leaf'.""" + return re.sub(r"(? at most one flat view directly under this family. + db = fetch_eplant_db(base_url, family, None, species_file) + if not db: + db = EPLANT_DB_OVERRIDE.get((site, family)) + if db: + views[_flat_view_label(family)] = db + + return views + + +def main(): + """Iterate over all eFP and ePlant sites, collect view-to-database mappings, and write output.""" + all_species_databases = {} + + for species, efp_url in EFP_SITES.items(): + print(f"[efp] Processing {species}...") + views = fetch_view_databases(species, efp_url) + if not views and species in _EFP_FALLBACK: + print(" Live scrape failed -- using last-known-good fallback") + views = _EFP_FALLBACK[species] + if views: + all_species_databases[f"efp_{species.replace(' ', '_')}"] = views + print(f" Found {len(views)} views") + else: + print(" No views found") + + for site, base_url in EPLANT_SITES.items(): + print(f"[eplant] Processing {site}...") + species_file = EPLANT_SPECIES_FILE[site] + families = EPLANT_FAMILIES[site] + views = fetch_eplant_views(site, base_url, species_file, families) + if views: + all_species_databases[site] = views + print(f" Found {len(views)} views") + else: + print(" No views found") + + out_file = "species_databases.json" + with open(out_file, "w") as f: + json.dump(all_species_databases, f, indent=2) + + print(f"\nOutput written to {out_file}") + + +if __name__ == "__main__": + main() diff --git a/species_databases.json b/species_databases.json new file mode 100644 index 0000000..85cff78 --- /dev/null +++ b/species_databases.json @@ -0,0 +1,368 @@ +{ + "efp_arabidopsis": { + "Abiotic Stress": "atgenexp_stress", + "Abiotic Stress II": "atgenexp_stress", + "Biotic Stress": "atgenexp_pathogen", + "Biotic Stress II": "atgenexp_pathogen", + "Chemical": "atgenexp_hormone", + "DNA Damage": "dna_damage", + "Development RMA": "atgenexp", + "Developmental Map": "atgenexp_plus", + "Developmental Mutants": "atgenexp_plus", + "Embryo": "embryo", + "Germination": "germination", + "Guard Cell": "guard_cell", + "Gynoecium": "gynoecium", + "Hormone": "atgenexp_hormone", + "Klepikova Atlas": "klepikova", + "Lateral Root Initiation": "lateral_root_initiation", + "Light Series": "light_series", + "Natural Variation": "arabidopsis_ecotypes", + "Regeneration": "meristem_db", + "Root": "root", + "Root II": "root", + "Seed": "seed_db", + "Shoot Apex": "shoot_apex", + "Silique": "silique", + "Single Cell": "single_cell", + "Tissue Specific": "atgenexp_plus" + }, + "efp_arabidopsis_lipid": { + "Lipid Map": "lipid_map" + }, + "efp_arabidopsis_cell": { + "Cell Type": "single_cell" + }, + "efp_arabidopsis_seedcoat": { + "Seed Coat": "seedcoat" + }, + "efp_poplar": { + "Poplar": "poplar", + "PoplarTreatment": "poplar" + }, + "efp_medicago": { + "medicago mas": "medicago_mas", + "medicago rma": "medicago_rma", + "medicago seed": "medicago_seed" + }, + "efp_soybean": { + "soybean": "soybean", + "soybean embryonic development": "soybean_embryonic_development", + "soybean heart cotyledon globular": "soybean_heart_cotyledon_globular", + "soybean senescence": "soybean_senescence", + "soybean severin": "soybean_severin" + }, + "efp_potato": { + "Potato Developmental": "potato_dev", + "Potato Stress": "potato_stress" + }, + "efp_tomato": { + "ILs Leaf Chitwood et al": "tomato_ils", + "ILs Root Tip Brady Lab": "tomato_ils2", + "M82 S pennellii Atlases Koenig et al": "tomato_s_pennellii", + "Rose Lab Atlas": "tomato", + "Rose Lab Atlas Renormalized": "tomato_renormalized", + "SEED Lab Angers": "tomato_seed", + "Shade Mutants": "tomato_shade_mutants", + "Shade Timecourse WT": "tomato_shade_timecourse", + "Tomato Meristem": "tomato_meristem" + }, + "efp_eutrema": { + "Eutrema": "thellungiella_db" + }, + "efp_camelina": { + "Developmental Atlas FPKM": "camelina", + "Developmental Atlas TPM": "camelina_tpm" + }, + "efp_arachis": { + "Arachis Atlas": "arachis" + }, + "efp_grape": { + "grape developmental": "grape_developmental" + }, + "efp_cannabis": { + "Cannabis Atlas": "cannabis" + }, + "efp_kalanchoe": { + "Light Response": "kalanchoe" + }, + "efp_actinidia": { + "Bud Development": "actinidia_bud_development", + "Flower Fruit Development": "actinidia_flower_fruit_development", + "Postharvest": "actinidia_postharvest", + "Vegetative Growth": "actinidia_vegetative_growth" + }, + "efp_brassica_rapa": { + "Embryogenesis": "brassica_rapa" + }, + "efp_canola": { + "Canola Seed": "canola_seed" + }, + "efp_cacao_ccn": { + "Developmental Atlas": "cacao_developmental_atlas", + "Drought Diurnal Atlas": "cacao_drought_diurnal_atlas" + }, + "efp_cacao_sca": { + "Developmental Atlas": "cacao_developmental_atlas_sca", + "Drought Diurnal Atlas": "cacao_drought_diurnal_atlas_sca", + "Meristem Atlas": "cacao_meristem_atlas_sca", + "Seed Atlas": "cacao_seed_atlas_sca" + }, + "efp_cacao_tc": { + "Cacao Infection": "cacao_infection", + "Cacao Leaf": "cacao_leaf" + }, + "efp_mangosteen": { + "Aril vs Rind": "mangosteen_aril_vs_rind", + "Callus": "mangosteen_callus", + "Diseased vs Normal": "mangosteen_diseased_vs_normal", + "Fruit Ripening": "mangosteen_fruit_ripening", + "Seed Development": "mangosteen_seed_development", + "Seed Germination": "mangosteen_seed_germination" + }, + "efp_lupin": { + "LCM Leaf": "lupin_lcm_leaf", + "LCM Pod": "lupin_lcm_pod", + "LCM Stem": "lupin_lcm_stem", + "Whole Plant": "lupin_whole_plant" + }, + "efp_strawberry": { + "Developmental Map Strawberry Flower and Fruit": "strawberry", + "Strawberry Green vs White Stage": "strawberry" + }, + "efp_maize": { + "Downs et al Atlas": "maize_gdowns", + "Early Seed": "maize_early_seed", + "Embryonic Leaf Development": "maize_embryonic_leaf_development", + "Hoopes et al Atlas": "maize_buell_lab", + "Hoopes et al Atlas V5": "maize_atlas_v5", + "Hoopes et al Stress": "maize_buell_lab", + "Hoopes et al Stress V5": "maize_stress_v5", + "Maize Kernel": "maize_early_seed", + "Maize Kernel V5": "maize_kernel_v5", + "Maize Root": "maize_root", + "Sekhon et al Atlas": "maize_RMA_linear", + "Tassel and Ear Primordia": "maize_ears", + "maize iplant": "maize_iplant", + "maize leaf gradient": "maize_leaf_gradient", + "maize rice comparison": "maize_rice_comparison" + }, + "efp_rice": { + "rice drought heat stress": "rice_drought_heat_stress", + "rice leaf gradient": "rice_leaf_gradient", + "rice maize comparison": "rice_maize_comparison", + "rice mas": "rice_mas", + "rice rma": "rice_rma", + "rice single cell": "rice_abiotic_stress_sc_pseudobulk", + "riceanoxia mas": "rice_mas", + "riceanoxia rma": "rice_rma", + "ricestigma mas": "rice_mas", + "ricestigma rma": "rice_rma", + "ricestress mas": "rice_mas", + "ricestress rma": "rice_rma" + }, + "efp_barley": { + "barley mas": "barley_mas", + "barley rma": "barley_rma" + }, + "efp_triticale": { + "triticale": "triticale", + "triticale mas": "triticale_mas" + }, + "efp_brachypodium": { + "Brachypodium Atlas": "brachypodium", + "Brachypodium Grains": "brachypodium_grains", + "Brachypodium Spikes": "brachypodium_Bd21", + "Photo Thermocycle": "brachypodium_photo_thermocycle" + }, + "efp_wheat": { + "Developmental Atlas": "wheat", + "Wheat Abiotic Stress": "wheat_abiotic_stress", + "Wheat Embryogenesis": "wheat_embryogenesis", + "Wheat Meiosis": "wheat_meiosis" + }, + "efp_little_millet": { + "Life Cycle": "little_millet" + }, + "efp_oat": { + "Oat": "oat" + }, + "efp_physcomitrella": { + "Physcomitrella": "physcomitrella_db" + }, + "efp_selaginella": { + "Selaginella Atlas": "selaginella" + }, + "efp_mouse": { + "Mouse": "mouse_db" + }, + "efp_human": { + "Circulatory Respiratory": "human_developmental", + "Illumina Body Map 2 - FPKM": "human_body_map_2", + "Nervous": "human_developmental", + "Reproductive": "human_developmental", + "Skeletal Immune Digestive": "human_developmental" + }, + "efp_phelipanche": { + "Phelipanche": "phelipanche" + }, + "efp_striga": { + "Striga Atlas": "striga" + }, + "efp_triphysaria": { + "Triphysaria": "triphysaria" + }, + "efp_durum_wheat": { + "Abiotic Stress": "durum_wheat_abiotic_stress", + "Biotic Stress": "durum_wheat_biotic_stress", + "Development": "durum_wheat_development" + }, + "efp_euphorbia": { + "Euphorbia": "euphorbia" + }, + "efp_marchantia": { + "Expression Atlas": "marchantia_organ_stress" + }, + "efp_sorghum": { + "Atlas w BS Cells": "sorghum_atlas_w_BS_cells", + "Developmental Atlas": "sorghum_developmental", + "Flowering Activation": "sorghum_flowering_activation", + "Low Phosphorus": "sorghum_low_phosphorus", + "Phosphate Stress": "sorghum_phosphate_stress", + "Saline Alkali Stress": "sorghum_saline_alkali_stress", + "Stress Atlas": "sorghum_stress", + "Strigolactone Variation": "sorghum_strigolactone_variation", + "Sulfur Stress": "sorghum_sulfur_stress", + "Vascularization and Internode": "sorghum_vascularization_and_internode" + }, + "efp_tung_tree": { + "Tung Tree": "tung_tree" + }, + "efp_apple": { + "Developmental Map": "apple" + }, + "efp_maize_enzyme": { + "Enzyme Activity": "maize_enzyme" + }, + "efp_maize_metabolite": { + "Metabolite Level": "maize_metabolite" + }, + "efp_rice_metabolite": { + "Metabolite Level": "rice_metabolite" + }, + "efp_brachypodium_metabolites": { + "Metabolite Level": "brachypodium_metabolites_map" + }, + "eplant_arabidopsis": { + "Cell": "single_cell", + "Abiotic Stress": "atgenexp_stress", + "Abiotic Stress II": "atgenexp_stress", + "Chemical": "atgenexp_hormone", + "DNA Damage": "dna_damage", + "Guard Cell Meristemoids": "guard_cell", + "Guard Cell Drought": "gc_drought", + "Guard Cell Mutant And Wild Type Guard Cell ABA Response": "guard_cell", + "Guard Cell Suspension Cell ABA Response With ROS Scavenger": "guard_cell", + "Tissue Specific Embryo Development": "atgenexp_plus", + "Tissue Specific Guard And Mesophyll Cells": "atgenexp_plus", + "Tissue Specific Microgametogenesis": "atgenexp_plus", + "Tissue Specific Pollen Germination": "atgenexp_plus", + "Tissue Specific Root": "root", + "Tissue Specific Shoot Apical Meristem": "atgenexp_plus", + "Tissue Specific Stem Epidermis": "atgenexp_plus", + "Tissue Specific Stigma And Ovaries": "atgenexp_plus", + "Tissue Specific Trichomes": "atgenexp_plus", + "Tissue Specific Xylem And Cork": "atgenexp_plus", + "Biotic Stress Botrytis cinerea": "atgenexp_pathogen", + "Biotic Stress Elicitors": "atgenexp_pathogen", + "Biotic Stress Erysiphe orontii": "atgenexp_pathogen", + "Biotic Stress Hyaloperonospora arabidopsidis": "atgenexp_pathogen", + "Biotic Stress Myzus persicaere": "atgenexp_pathogen", + "Biotic Stress Phytophthora infestans": "atgenexp_pathogen", + "Biotic Stress Pseudomonas syringae": "atgenexp_pathogen", + "Biotic Stress Golovinomyces orontii": "atgenexp_pathogen", + "Root Immunity Elicitation": "root_Schaefer_lab", + "Germination": "germination", + "Heterodera schachtii": "heterodera_schachtii", + "Shoot Apex": "shoot_apex", + "Single Cell": "single_cell", + "AtGenExpress": "atgenexp_plus", + "Klepikova": "klepikova" + }, + "eplant_maize": { + "Root": "maize_root", + "Sekhon Atlas": "maize_RMA_linear", + "Tassel And Ear Primordia": "maize_ears", + "Leaf Gradient": "maize_leaf_gradient", + "Leaf MeBS": "maize_iplant", + "Plant": "maize_gdowns" + }, + "eplant_poplar": { + "Poplar Treatment": "poplar", + "Plant": "poplar", + "World Leaf": "poplar_leaf", + "World Xylem": "poplar_xylem" + }, + "eplant_tomato": { + "Fruit": "tomato_renormalized", + "TomatoAtlases": "tomato_s_pennellii", + "LeafILs": "tomato_ils", + "RootILs": "tomato_ils2", + "Root": "tomato_root", + "RootFieldPot": "tomato_root_field_pot", + "Plant": "tomato_renormalized" + }, + "eplant_camelina": { + "Plant": "camelina" + }, + "eplant_soybean": { + "Soybean Severin": "soybean_severin", + "Plant": "soybean" + }, + "eplant_potato": { + "Potato Stress": "potato_stress", + "Plant": "potato_dev" + }, + "eplant_barley": { + "Seed": "barley_seed", + "Spike Meristem": "barley_spike_meristem_v3", + "Spike Meristem Shade Response": "barley_spike_meristem_v3" + }, + "eplant_barley_legacy": { + "Spike Meristem": "barley_spike_meristem", + "Spike Meristem Shade Response": "barley_spike_meristem" + }, + "eplant_medicago": { + "Seed": "medicago_seed", + "Root": "medicago_root", + "Root Component": "medicago_root", + "Plant": "medicago_mas" + }, + "eplant_eucalyptus": { + "Stress": "eucalyptus", + "Plant": "eucalyptus" + }, + "eplant_rice": { + "Anoxia": "rice_mas", + "Stress": "rice_mas", + "Stigma": "rice_mas", + "Leaf Gradient": "rice_leaf_gradient", + "Root": "rice_root", + "Plant": "rice_mas" + }, + "eplant_sunflower": { + "Plant": "sunflower" + }, + "eplant_cannabis": { + "Plant": "cannabis" + }, + "eplant_wheat": { + "EarlyStages": "wheat", + "MiddleStages": "wheat", + "LateStages": "wheat" + }, + "eplant_sugarcane": { + "Leaf": "sugarcane_leaf", + "Culms": "sugarcane_culms" + } +} \ No newline at end of file diff --git a/tests/resources/test_eplant_arabidopsis.py b/tests/resources/test_eplant_arabidopsis.py new file mode 100644 index 0000000..785c3ca --- /dev/null +++ b/tests/resources/test_eplant_arabidopsis.py @@ -0,0 +1,88 @@ +""" +Reena Obmina | UTEA Project 2026 | University of Toronto + +Tests for the ePlant Arabidopsis expression endpoint. + +Route: GET /expression/ePlant_expression?gene=AT1G01010&species=Arabidopsis + +The external plantefp.cgi call inside get_expression() is mocked so tests +run without a network connection to bar.utoronto.ca. + +Usage:: + + python3 -m pytest tests/resources/test_eplant_arabidopsis.py -v +""" +from api import app +from unittest import TestCase +from unittest.mock import patch + +_MOCK_RESULT = { + "gene": "AT1G01010", + "views": { + "atgenexpress": { + "groups": [ + { + "name": "CTRL_7", + "controls": {"ATGE_CTRL_7": 13.05}, + "tissues": [ + { + "name": "Root", + "id": "Root", + "samples": {"ATGE_9_A": 45.35, "ATGE_9_B": 55.0}, + } + ], + } + ] + } + }, +} + + +class TestEPlantArabidopsisExpression(TestCase): + def setUp(self): + self.client = app.test_client() + + @patch("api.resources.expression.get_expression", return_value=_MOCK_RESULT) + def test_valid_request(self, _mock): + response = self.client.get("/expression/ePlant_expression?gene=AT1G01010&species=Arabidopsis") + self.assertEqual(response.status_code, 200) + data = response.json + self.assertTrue(data["wasSuccessful"]) + self.assertEqual(data["data"]["gene"], "AT1G01010") + self.assertIn("views", data["data"]) + _mock.assert_called_once_with("AT1G01010") + + @patch("api.resources.expression.get_expression", return_value=_MOCK_RESULT) + def test_gene_uppercased(self, _mock): + """Gene IDs are normalised to uppercase before being forwarded.""" + self.client.get("/expression/ePlant_expression?gene=at1g01010&species=Arabidopsis") + _mock.assert_called_once_with("AT1G01010") + + @patch("api.resources.expression.get_expression", return_value=_MOCK_RESULT) + def test_species_case_insensitive(self, _mock): + response = self.client.get("/expression/ePlant_expression?gene=AT1G01010&species=arabidopsis") + self.assertEqual(response.status_code, 200) + self.assertTrue(response.json["wasSuccessful"]) + + @patch("api.resources.expression.get_expression", return_value=_MOCK_RESULT) + def test_arabidopsis_thaliana_species(self, _mock): + response = self.client.get( + "/expression/ePlant_expression?gene=AT1G01010&species=Arabidopsis+thaliana" + ) + self.assertEqual(response.status_code, 200) + self.assertTrue(response.json["wasSuccessful"]) + + def test_missing_gene(self): + response = self.client.get("/expression/ePlant_expression?species=Arabidopsis") + self.assertEqual(response.status_code, 400) + self.assertFalse(response.json["wasSuccessful"]) + + def test_invalid_gene(self): + response = self.client.get("/expression/ePlant_expression?gene=NOTAGENEID&species=Arabidopsis") + self.assertEqual(response.status_code, 400) + self.assertFalse(response.json["wasSuccessful"]) + + def test_invalid_species(self): + response = self.client.get("/expression/ePlant_expression?gene=AT1G01010&species=potato") + self.assertEqual(response.status_code, 400) + self.assertFalse(response.json["wasSuccessful"]) diff --git a/tests/resources/test_gene_expression.py b/tests/resources/test_gene_expression.py new file mode 100644 index 0000000..9cf9b6e --- /dev/null +++ b/tests/resources/test_gene_expression.py @@ -0,0 +1,261 @@ +""" +Tests for the /gene_expression/expression// endpoint. + +Covers three important cases: + 1. Gene ID validation — valid/invalid inputs per database. + 2. Probeset ID input — actual probeset IDs from sample data (no AGI conversion needed). + 3. AGI input for Arabidopsis microarray databases — verifies the AGI→probeset lookup path + is accepted (data retrieval itself is tested in CI where the lookup DB is present). + +Sample probeset IDs are drawn from the JSON files in +.github/workflows/random_rows_json/ to ensure we test with real IDs, not synthetic ones. +""" +from unittest import TestCase + +from api import app +from api.utils.gene_id_utils import GeneIdUtils, DATABASE_EFP_PROJECT + + +class TestGeneExpressionValidation(TestCase): + """Validate that the endpoint accepts and rejects the right gene ID formats.""" + + def setUp(self): + self.client = app.test_client() + + # --- Arabidopsis AGI input (microarray databases) --- + + def test_arabidopsis_agi_accepted_for_microarray_db(self): + """An Arabidopsis AGI is accepted for a microarray-backed database.""" + # The endpoint validates the format; actual data retrieval depends on DB availability + response = self.client.get("/gene_expression/expression/light_series/AT2G21130") + # Should not be a 400 validation error + self.assertNotEqual(response.status_code, 400) + + def test_arabidopsis_agi_case_insensitive(self): + """AGI IDs are accepted regardless of case.""" + response = self.client.get("/gene_expression/expression/light_series/at2g21130") + self.assertNotEqual(response.status_code, 400) + + def test_invalid_arabidopsis_gene_rejected(self): + """A clearly invalid gene ID is rejected with 400.""" + response = self.client.get("/gene_expression/expression/light_series/NOTAGENEID") + self.assertEqual(response.status_code, 400) + self.assertFalse(response.json["wasSuccessful"]) + + # --- Arabidopsis ATH1 probeset IDs (passed directly) --- + + def test_arabidopsis_probeset_accepted_light_series(self): + """An ATH1 probeset ID is accepted for the light_series database.""" + # 263677_at is a real probe from light_series_test_data.json + response = self.client.get("/gene_expression/expression/light_series/263677_at") + self.assertNotEqual(response.status_code, 400) + + def test_arabidopsis_probeset_s_at_accepted(self): + """A _s_at probeset ID is accepted for an Arabidopsis microarray database.""" + # 261283_s_at is a real probe from affydb_test_data.json + response = self.client.get("/gene_expression/expression/affydb/261283_s_at") + self.assertNotEqual(response.status_code, 400) + + def test_arabidopsis_probeset_accepted_atgenexp(self): + """A numeric ATH1 probeset is accepted for the atgenexp database.""" + response = self.client.get("/gene_expression/expression/atgenexp/253680_at") + self.assertNotEqual(response.status_code, 400) + + # --- Seedcoat CATMA/AROS probes --- + + def test_seedcoat_catma_probe_accepted(self): + """A CATMA probe (At + 8 digits) is accepted for the seedcoat database.""" + # At30023977 is a real probe from seedcoat_test_data.json + response = self.client.get("/gene_expression/expression/seedcoat/At30023977") + self.assertNotEqual(response.status_code, 400) + + def test_seedcoat_aros_probe_accepted(self): + """An AROS probe (non-digit + digits + underscore + digits) is accepted for seedcoat.""" + # A017813_01 is a real probe from seedcoat_test_data.json + response = self.client.get("/gene_expression/expression/seedcoat/A017813_01") + self.assertNotEqual(response.status_code, 400) + + def test_seedcoat_invalid_probe_rejected(self): + """A random string is rejected for the seedcoat database.""" + response = self.client.get("/gene_expression/expression/seedcoat/NOTAPROBE") + self.assertEqual(response.status_code, 400) + + # --- Barley microarray probesets --- + + def test_barley_probeset_accepted_mas(self): + """A Contig*_at barley probeset is accepted for barley_mas.""" + # Contig7905_at is a real probe from barley_mas_test_data.json + response = self.client.get("/gene_expression/expression/barley_mas/Contig7905_at") + self.assertNotEqual(response.status_code, 400) + + def test_barley_probeset_accepted_rma(self): + """Complex barley probesets are accepted for barley_rma.""" + # EBro06_SQ001_B02_at is a real probe from barley_rma_test_data.json + response = self.client.get("/gene_expression/expression/barley_rma/EBro06_SQ001_B02_at") + self.assertNotEqual(response.status_code, 400) + + def test_barley_invalid_probe_rejected(self): + """An invalid ID is rejected for barley databases.""" + response = self.client.get("/gene_expression/expression/barley_mas/NOTAPROBE!!!") + self.assertEqual(response.status_code, 400) + + # --- Rice microarray probesets --- + + def test_rice_mas_probeset_accepted(self): + """A rice Os.*_at probeset is accepted for rice_mas.""" + # Os.17822.2.S1_s_at is a real probe from rice_mas_test_data.json + response = self.client.get("/gene_expression/expression/rice_mas/Os.17822.2.S1_s_at") + self.assertNotEqual(response.status_code, 400) + + def test_rice_rma_affx_probeset_accepted(self): + """An OsAffx probeset is accepted for rice_rma.""" + # OsAffx.13653.1.S1_at is a real probe from rice_rma_test_data.json + response = self.client.get("/gene_expression/expression/rice_rma/OsAffx.13653.1.S1_at") + self.assertNotEqual(response.status_code, 400) + + def test_rice_gene_id_accepted(self): + """A canonical LOC_Os rice gene ID is accepted for rice_mas.""" + response = self.client.get("/gene_expression/expression/rice_mas/LOC_Os01g01430") + self.assertNotEqual(response.status_code, 400) + + def test_rice_invalid_id_rejected(self): + """An invalid ID is rejected for rice databases.""" + response = self.client.get("/gene_expression/expression/rice_mas/NOTAPROBE") + self.assertEqual(response.status_code, 400) + + # --- Medicago microarray probesets --- + + def test_medicago_mtr_probeset_accepted(self): + """A Mtr probeset is accepted for medicago_mas.""" + # Mtr.44080.1.S1_at is a real probe from medicago_mas_test_data.json + response = self.client.get("/gene_expression/expression/medicago_mas/Mtr.44080.1.S1_at") + self.assertNotEqual(response.status_code, 400) + + def test_medicago_msa_probeset_accepted(self): + """A Msa probeset is accepted for medicago_rma.""" + # Msa.959.1.S1_at is a real probe from medicago_mas_test_data.json + response = self.client.get("/gene_expression/expression/medicago_rma/Msa.959.1.S1_at") + self.assertNotEqual(response.status_code, 400) + + def test_medicago_sme_probeset_accepted(self): + """A Sme probeset is accepted for medicago databases.""" + # Sme.396.1.S1_at is a real probe from medicago_rma_test_data.json + response = self.client.get("/gene_expression/expression/medicago_rma/Sme.396.1.S1_at") + self.assertNotEqual(response.status_code, 400) + + # --- Poplar microarray probesets --- + + def test_poplar_ptpaffx_probeset_accepted(self): + """A PtpAffx probeset is accepted for the poplar database.""" + # PtpAffx.154622.1.S1_at is a real probe from poplar_test_data.json + response = self.client.get("/gene_expression/expression/poplar/PtpAffx.154622.1.S1_at") + self.assertNotEqual(response.status_code, 400) + + def test_poplar_ptp_s_at_probeset_accepted(self): + """A PtpAffx _s_at probeset is accepted for the poplar database.""" + # PtpAffx.202274.1.S1_s_at is a real probe from poplar_test_data.json + response = self.client.get( + "/gene_expression/expression/poplar/PtpAffx.202274.1.S1_s_at" + ) + self.assertNotEqual(response.status_code, 400) + + # --- Triticale microarray probesets --- + + def test_triticale_probeset_accepted(self): + """A Ta.*_at triticale probeset is accepted for the triticale database.""" + # Ta.8002.1.S1_at is a real probe from triticale_test_data.json + response = self.client.get("/gene_expression/expression/triticale/Ta.8002.1.S1_at") + self.assertNotEqual(response.status_code, 400) + + # --- Unknown database --- + + def test_unknown_database_rejected(self): + """An unknown database name returns an error response.""" + response = self.client.get( + "/gene_expression/expression/totally_unknown_database/AT1G01010" + ) + self.assertFalse(response.json.get("wasSuccessful", True)) + + +class TestGeneIdUtilsDatabase(TestCase): + """Unit tests for validate_gene_for_database() and DATABASE_EFP_PROJECT mapping.""" + + def test_database_efp_project_has_microarray_dbs(self): + """All expected microarray databases must have an eFP project mapping.""" + expected_dbs = [ + "affydb", "arabidopsis_ecotypes", "atgenexp", "light_series", + "seedcoat", + "barley_mas", "barley_rma", + "rice_mas", "rice_rma", + "medicago_mas", "medicago_rma", + "poplar", + "triticale", "triticale_mas", + ] + for db in expected_dbs: + self.assertIn(db, DATABASE_EFP_PROJECT, f"Missing DATABASE_EFP_PROJECT entry for {db}") + + def test_validate_arabidopsis_agi(self): + """AGI IDs are valid for arabidopsis microarray databases.""" + self.assertTrue(GeneIdUtils.validate_gene_for_database("AT1G01010", "light_series")) + self.assertTrue(GeneIdUtils.validate_gene_for_database("AT2G21130", "affydb")) + + def test_validate_arabidopsis_probeset(self): + """ATH1 probeset IDs are valid for arabidopsis microarray databases.""" + self.assertTrue(GeneIdUtils.validate_gene_for_database("267643_at", "light_series")) + self.assertTrue(GeneIdUtils.validate_gene_for_database("261283_s_at", "affydb")) + + def test_validate_seedcoat_catma_probe(self): + """CATMA probe IDs are valid for the seedcoat database.""" + self.assertTrue(GeneIdUtils.validate_gene_for_database("At30023977", "seedcoat")) + self.assertTrue(GeneIdUtils.validate_gene_for_database("At30027789", "seedcoat")) + + def test_validate_seedcoat_aros_probe(self): + """AROS probe IDs are valid for the seedcoat database.""" + self.assertTrue(GeneIdUtils.validate_gene_for_database("A017813_01", "seedcoat")) + + def test_validate_barley_probeset(self): + """Barley probeset IDs are valid for barley microarray databases.""" + self.assertTrue(GeneIdUtils.validate_gene_for_database("Contig7905_at", "barley_mas")) + self.assertTrue( + GeneIdUtils.validate_gene_for_database("EBro06_SQ001_B02_at", "barley_rma") + ) + + def test_validate_rice_probeset(self): + """Rice probeset IDs are valid for rice microarray databases.""" + self.assertTrue(GeneIdUtils.validate_gene_for_database("Os.17822.2.S1_s_at", "rice_mas")) + self.assertTrue(GeneIdUtils.validate_gene_for_database("OsAffx.13653.1.S1_at", "rice_rma")) + + def test_validate_medicago_probeset(self): + """Medicago probeset IDs are valid for medicago microarray databases.""" + self.assertTrue(GeneIdUtils.validate_gene_for_database("Mtr.44080.1.S1_at", "medicago_mas")) + self.assertTrue(GeneIdUtils.validate_gene_for_database("Sme.396.1.S1_at", "medicago_rma")) + + def test_validate_poplar_probeset(self): + """Poplar probeset IDs are valid for the poplar microarray database.""" + self.assertTrue(GeneIdUtils.validate_gene_for_database("PtpAffx.154622.1.S1_at", "poplar")) + + def test_validate_triticale_probeset(self): + """Triticale probeset IDs are valid for the triticale database.""" + self.assertTrue(GeneIdUtils.validate_gene_for_database("Ta.8002.1.S1_at", "triticale")) + + def test_is_probeset_id_detects_catma_probe(self): + """CATMA probes (At + 8 digits) are recognised as probeset IDs.""" + self.assertTrue(GeneIdUtils.is_probeset_id("At30023977")) + self.assertTrue(GeneIdUtils.is_probeset_id("At30027789")) + + def test_is_probeset_id_detects_affymetrix_probe(self): + """Standard _at probes are recognised as probeset IDs.""" + self.assertTrue(GeneIdUtils.is_probeset_id("267643_at")) + self.assertTrue(GeneIdUtils.is_probeset_id("Contig7905_at")) + self.assertTrue(GeneIdUtils.is_probeset_id("Os.17822.2.S1_s_at")) + + def test_is_probeset_id_rejects_gene_ids(self): + """Canonical gene IDs are NOT treated as probeset IDs.""" + self.assertFalse(GeneIdUtils.is_probeset_id("AT1G01010")) + self.assertFalse(GeneIdUtils.is_probeset_id("LOC_Os01g01430")) + self.assertFalse(GeneIdUtils.is_probeset_id("randomjunk")) + + def test_validate_gene_for_non_efp_database_falls_back_to_species(self): + """Non-microarray databases use species-based validation.""" + self.assertTrue(GeneIdUtils.validate_gene_for_database("AT1G01010", "klepikova")) + self.assertFalse(GeneIdUtils.validate_gene_for_database("NOTAGENEID", "klepikova")) diff --git a/tests/utils/test_bar_utils.py b/tests/utils/test_bar_utils.py index 7396d66..c16a5fb 100644 --- a/tests/utils/test_bar_utils.py +++ b/tests/utils/test_bar_utils.py @@ -1,5 +1,5 @@ from unittest import TestCase -from api.utils.bar_utils import BARUtils +from api.utils.bar_utils import BARUtils, EFP_PROJECT_REGEXES class UtilsUnitTest(TestCase): @@ -149,3 +149,117 @@ def test_format_poplar(self): result = BARUtils.format_poplar("potri.019g123900.1") expected = "Potri.019G123900.1" self.assertEqual(result, expected) + + def test_efp_project_regexes_exist(self): + """All expected eFP project keys must be present in EFP_PROJECT_REGEXES.""" + required = [ + "efp", "efp_arabidopsis", "efp_seedcoat", + "efp_barley", "efpbarley", + "efp_rice", "efprice", + "efp_medicago", "efpmedicago", + "efp_poplar", "efppop", + "efp_soybean", "efpsoybean", + "efp_maize", "maizeefp", + "efp_triticale", + "efp_human", + ] + for key in required: + self.assertIn(key, EFP_PROJECT_REGEXES, f"Missing eFP project key: {key}") + + def test_is_efp_gene_valid_arabidopsis(self): + """efp_arabidopsis accepts AGI, ATH1 probeset IDs, and standalone numerics.""" + # Valid canonical AGI gene IDs + self.assertTrue(BARUtils.is_efp_gene_valid("AT2G21130", "efp_arabidopsis")) + self.assertTrue(BARUtils.is_efp_gene_valid("At1g01010", "efp_arabidopsis")) + self.assertTrue(BARUtils.is_efp_gene_valid("AtCg00020", "efp_arabidopsis")) + + # Valid Arabidopsis ATH1 probeset IDs (from sample data) + self.assertTrue(BARUtils.is_efp_gene_valid("267643_at", "efp_arabidopsis")) + self.assertTrue(BARUtils.is_efp_gene_valid("267644_s_at", "efp_arabidopsis")) + self.assertTrue(BARUtils.is_efp_gene_valid("261283_s_at", "efp_arabidopsis")) + self.assertTrue(BARUtils.is_efp_gene_valid("253680_at", "efp_arabidopsis")) + + # Valid standalone numeric IDs + self.assertTrue(BARUtils.is_efp_gene_valid("267643", "efp_arabidopsis")) + + # Invalid IDs + self.assertFalse(BARUtils.is_efp_gene_valid("9T2G21130", "efp_arabidopsis")) + self.assertFalse(BARUtils.is_efp_gene_valid("AT2G2113X", "efp_arabidopsis")) + self.assertFalse(BARUtils.is_efp_gene_valid("Solyc04g054700", "efp_arabidopsis")) + self.assertFalse(BARUtils.is_efp_gene_valid("randomjunk", "efp_arabidopsis")) + + def test_is_efp_gene_valid_seedcoat(self): + """efp_seedcoat accepts AGI, ATH1 probesets, CATMA probes, and AROS probes.""" + self.assertTrue(BARUtils.is_efp_gene_valid("At1g01010", "efp_seedcoat")) + self.assertTrue(BARUtils.is_efp_gene_valid("At30023977", "efp_seedcoat")) + self.assertTrue(BARUtils.is_efp_gene_valid("At30027789", "efp_seedcoat")) + self.assertTrue(BARUtils.is_efp_gene_valid("A017813_01", "efp_seedcoat")) + self.assertTrue(BARUtils.is_efp_gene_valid("A006881_01", "efp_seedcoat")) + self.assertFalse(BARUtils.is_efp_gene_valid("randomjunk", "efp_seedcoat")) + + def test_is_efp_gene_valid_barley(self): + """efp_barley accepts barley gene IDs and Affymetrix barley probeset IDs.""" + # Probeset IDs from barley_mas and barley_rma sample data + self.assertTrue(BARUtils.is_efp_gene_valid("Contig7905_at", "efp_barley")) + self.assertTrue(BARUtils.is_efp_gene_valid("Contig440_s_at", "efp_barley")) + self.assertTrue(BARUtils.is_efp_gene_valid("EBro06_SQ001_B02_at", "efp_barley")) + self.assertTrue(BARUtils.is_efp_gene_valid("HVSMEi0007J05r2_at", "efp_barley")) + self.assertTrue(BARUtils.is_efp_gene_valid("Contig12089_at", "efp_barley")) + # efpbarley alias + self.assertTrue(BARUtils.is_efp_gene_valid("Contig7905_at", "efpbarley")) + + self.assertFalse(BARUtils.is_efp_gene_valid("AT1G01010", "efp_barley")) + self.assertFalse(BARUtils.is_efp_gene_valid("randomjunk", "efp_barley")) + + def test_is_efp_gene_valid_rice(self): + """efp_rice accepts canonical rice gene IDs and rice array probeset IDs.""" + self.assertTrue(BARUtils.is_efp_gene_valid("LOC_Os01g01430", "efp_rice")) + self.assertTrue(BARUtils.is_efp_gene_valid("Os.17822.2.S1_s_at", "efp_rice")) + self.assertTrue(BARUtils.is_efp_gene_valid("OsAffx.4511.1.S1_s_at", "efp_rice")) + self.assertTrue(BARUtils.is_efp_gene_valid("Os.12223.2.S1_at", "efp_rice")) + # efprice alias + self.assertTrue(BARUtils.is_efp_gene_valid("LOC_Os01g01430", "efprice")) + + self.assertFalse(BARUtils.is_efp_gene_valid("AT1G01010", "efp_rice")) + self.assertFalse(BARUtils.is_efp_gene_valid("randomjunk", "efp_rice")) + + def test_is_efp_gene_valid_medicago(self): + """efp_medicago accepts canonical Medicago gene IDs and Medicago array probeset IDs.""" + self.assertTrue(BARUtils.is_efp_gene_valid("Medtr1g018805", "efp_medicago")) + self.assertTrue(BARUtils.is_efp_gene_valid("Mtr.44080.1.S1_at", "efp_medicago")) + self.assertTrue(BARUtils.is_efp_gene_valid("Msa.959.1.S1_at", "efp_medicago")) + self.assertTrue(BARUtils.is_efp_gene_valid("Sme.396.1.S1_at", "efp_medicago")) + # _s_at variants must also match (e.g. Mtr.50680.1.S1_s_at from medicago_rma) + self.assertTrue(BARUtils.is_efp_gene_valid("Mtr.50680.1.S1_s_at", "efp_medicago")) + # efpmedicago alias + self.assertTrue(BARUtils.is_efp_gene_valid("Medtr1g018805", "efpmedicago")) + + self.assertFalse(BARUtils.is_efp_gene_valid("AT1G01010", "efp_medicago")) + self.assertFalse(BARUtils.is_efp_gene_valid("randomjunk", "efp_medicago")) + + def test_is_efp_gene_valid_poplar(self): + """efp_poplar accepts Potri gene IDs and poplar array probeset IDs.""" + self.assertTrue(BARUtils.is_efp_gene_valid("Potri.019G123900.1", "efp_poplar")) + self.assertTrue(BARUtils.is_efp_gene_valid("PtpAffx.154622.1.S1_at", "efp_poplar")) + self.assertTrue(BARUtils.is_efp_gene_valid("PtpAffx.37687.1.S1_at", "efp_poplar")) + self.assertTrue(BARUtils.is_efp_gene_valid("PtpAffx.202274.1.S1_s_at", "efp_poplar")) + # efppop alias + self.assertTrue(BARUtils.is_efp_gene_valid("PtpAffx.154622.1.S1_at", "efppop")) + + self.assertFalse(BARUtils.is_efp_gene_valid("AT1G01010", "efp_poplar")) + self.assertFalse(BARUtils.is_efp_gene_valid("randomjunk", "efp_poplar")) + + def test_is_efp_gene_valid_triticale(self): + """efp_triticale accepts Ta.* and TaAffx.* probeset IDs (both occur in data).""" + self.assertTrue(BARUtils.is_efp_gene_valid("Ta.8002.1.S1_at", "efp_triticale")) + # TaAffx probes from triticale_test_data.json — require TaAffx prefix support + self.assertTrue(BARUtils.is_efp_gene_valid("TaAffx.54155.1.S1_at", "efp_triticale")) + self.assertTrue(BARUtils.is_efp_gene_valid("TaAffx.6560.1.S1_at", "efp_triticale")) + self.assertTrue(BARUtils.is_efp_gene_valid("Ta.3469.1.A1_at", "efp_triticale")) + + self.assertFalse(BARUtils.is_efp_gene_valid("randomjunk", "efp_triticale")) + self.assertFalse(BARUtils.is_efp_gene_valid("AT1G01010", "efp_triticale")) + + def test_is_efp_gene_valid_unknown_project(self): + """Unknown eFP project returns False regardless of gene ID.""" + self.assertFalse(BARUtils.is_efp_gene_valid("AT1G01010", "efp_unknown_species")) diff --git a/validate_db_regex_coverage.py b/validate_db_regex_coverage.py new file mode 100644 index 0000000..13a4d0f --- /dev/null +++ b/validate_db_regex_coverage.py @@ -0,0 +1,137 @@ +""" +Reena Obmina | BCB330 Project 2025-2026 | University of Toronto + +Task 2 (Jun 11 2026): test Vincent's per-project eFP regexes against every +database that has real sample data in api/random_rows_json/, to find +databases whose probeset/gene IDs the current production validator +(GeneIdUtils.validate_gene_for_database) would incorrectly reject. + +The universe tested is the FULL random_rows_json folder, not just the +databases reachable from a live eFP/ePlant dropdown today (data/efp_info/ +db_source_summary.json) -- some databases Vincent has sample data for are no +longer linked from any current dropdown (legacy/retired views) but are still +queryable directly by db name and already validator-ready (DATABASE_SPECIES / +DATABASE_EFP_PROJECT), so they're tested too and flagged via in_master_list. + +Reads: api/random_rows_json/{db}_test_data.json — real sample rows, one file per db + data/efp_info/db_source_summary.json — db -> efp/eplant/both, for dbs reachable live + api/utils/gene_id_utils.py / bar_utils.py — current production validators +Writes: db_regex_coverage_report.csv — one row per db: pass/fail counts + gap flag +""" + +import csv +import json +import sys +import types +from pathlib import Path + +# importing api.utils.gene_id_utils normally runs api/__init__.py's create_app(), +# which tries to connect to MySQL even for this standalone script. Pre-register +# empty stand-in packages so Python loads the submodules directly instead. +sys.modules.setdefault("api", types.ModuleType("api")) +sys.modules["api"].__path__ = ["api"] +sys.modules.setdefault("api.utils", types.ModuleType("api.utils")) +sys.modules["api.utils"].__path__ = ["api/utils"] + +from api.utils.gene_id_utils import DATABASE_EFP_PROJECT, DATABASE_SPECIES, GeneIdUtils # noqa: E402 + +SAMPLE_DIR = Path("api/random_rows_json") + + +def load_samples(db): + path = SAMPLE_DIR / f"{db}_test_data.json" + if not path.exists(): + return None + with open(path) as f: + rows = json.load(f) + ids = [] + seen = set() + for row in rows: + gene_id = row.get("data_probeset_id") + if gene_id and gene_id not in seen: + seen.add(gene_id) + ids.append(gene_id) + return ids + + +def main(): + with open("data/efp_info/db_source_summary.json") as f: + db_sources = json.load(f) + + sample_dbs = {p.name[: -len("_test_data.json")] for p in SAMPLE_DIR.glob("*_test_data.json")} + all_dbs = sample_dbs | set(db_sources) + + report_rows = [] + gap_count = 0 + no_sample_count = 0 + no_species_mapping_count = 0 + + for db in sorted(all_dbs): + source = db_sources.get(db, "legacy_not_in_dropdown") + sample_ids = load_samples(db) + if sample_ids is None: + no_sample_count += 1 + report_rows.append( + { + "database": db, + "source": source, + "in_master_list": db in db_sources, + "has_species_mapping": db in DATABASE_SPECIES, + "has_efp_project_override": db in DATABASE_EFP_PROJECT, + "n_samples": 0, + "n_pass": 0, + "n_fail": 0, + "looks_like_probeset": "", + "failing_ids": "NO SAMPLE DATA", + } + ) + continue + if db not in DATABASE_SPECIES and db not in DATABASE_EFP_PROJECT: + no_species_mapping_count += 1 + + n_pass = 0 + failing_ids = [] + any_probeset_shaped = False + for gene_id in sample_ids: + if GeneIdUtils.is_probeset_id(gene_id): + any_probeset_shaped = True + if GeneIdUtils.validate_gene_for_database(gene_id, db): + n_pass += 1 + else: + failing_ids.append(gene_id) + + is_gap = bool(failing_ids) + if is_gap: + gap_count += 1 + + report_rows.append( + { + "database": db, + "source": source, + "in_master_list": db in db_sources, + "has_species_mapping": db in DATABASE_SPECIES, + "has_efp_project_override": db in DATABASE_EFP_PROJECT, + "n_samples": len(sample_ids), + "n_pass": n_pass, + "n_fail": len(failing_ids), + "looks_like_probeset": any_probeset_shaped, + "failing_ids": "|".join(failing_ids[:5]), + } + ) + + out_file = "db_regex_coverage_report.csv" + with open(out_file, "w", newline="") as f: + writer = csv.DictWriter(f, fieldnames=list(report_rows[0].keys())) + writer.writeheader() + writer.writerows(report_rows) + + print(f"Checked {len(all_dbs)} databases ({len(db_sources)} in live master list, " + f"{len(all_dbs) - len(db_sources)} legacy/not currently linked from any dropdown).") + print(f" No sample data found: {no_sample_count}") + print(f" No species/eFP-project mapping at all: {no_species_mapping_count}") + print(f" Databases with >=1 real sample ID rejected by current validation: {gap_count}") + print(f"Report written to {out_file}") + + +if __name__ == "__main__": + main()