Merge pull request #1 from iibadshah/main

Adding ks datasets

Author: CutillasLab

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: protools2
 Type: Package
 Title: A set of tools for proteomics and phosphoproteomics data analysis
-Version: 0.1.0
+Version: 0.2.1
 Date: 2023-01-07
 Author: Pedro Rodriguez Cutillas
 Maintainer: Pedro Rodriguez Cutillas <p.cutillas@qmul.ac.uk>
@@ -22,4 +22,4 @@ Imports:
     limma,
     readxl,
     stringr
-RoxygenNote: 7.2.1
+RoxygenNote: 7.2.3

data-raw/Kinase_Substrate_Dataset_psite_2023_05.csv

@@ -0,0 +1,316 @@
+# Load packages ----
+library(devtools)
+library(dplyr)
+
+
+# Create species-specific PhosphoSitePlus data ----
+
+# Load PhoshoSitePlus data
+# Available from: https://www.phosphosite.org/staticDownloads
+psite_Kinase_Substrate_Dataset <- read.csv("Kinase_Substrate_Dataset_psite_2023_05.csv")
+
+# Get unique species in dataset
+species_kin <- unique(psite_Kinase_Substrate_Dataset$KIN_ORGANISM)
+species_sub <- unique(psite_Kinase_Substrate_Dataset$SUB_ORGANISM)
+species_list <- dplyr::intersect(species_kin, species_sub)
+
+# Create dataframe in `protools2` required format
+psite_ks_species <- vector("list", length = length(species_list))
+names(psite_ks_species) <- paste0("psite_", species_list)
+for (species in species_list) {
+  psite_ks_species[[paste0("psite_", species)]] <- psite_Kinase_Substrate_Dataset %>%
+    dplyr::filter(KIN_ORGANISM == species & SUB_ORGANISM == species) %>%  # Filters matching species
+    dplyr::group_by(GENE) %>%
+    dplyr::summarise(
+      m = dplyr::n(),
+      subs = paste0(SUB_GENE, "(", SUB_MOD_RSD, ")", collapse = ";")
+    ) %>%
+    dplyr::mutate(
+      organism = species,
+      gene.db = paste0(GENE, ".pSite")
+    ) %>%
+    dplyr::rename(gene = GENE)
+}
+
+# Save the processed data (saves to 'data/psite_ks_species.rda')
+usethis::use_data(psite_ks_species)
+
+
+#####
+
+jj <- 1
+
+if (jj == 1) {
+  edges <- "https://www.dropbox.com/s/ttmzd40mnjgh1iu/edges.csv?dl=1"
+  pdts <- "https://www.dropbox.com/s/86jfnayv0qa1n2q/pdts.csv?dl=1"
+  psite <- "https://www.dropbox.com/s/eb1qoofz793f4tq/psite.csv?dl=1"
+  signor <- "https://www.dropbox.com/s/alpbq880emz1z2t/signor.csv?dl=1"
+  reactome <- "https://www.dropbox.com/s/jdcc1355cz73mmi/reactome.csv?dl=1"
+
+  process <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/process_ont.csv"
+  myfunction <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/function_ont.csv"
+  location <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/location_ont.csv"
+
+  process_mouse <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/process_ont_mouse.csv"
+  myfunction_mouse <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/function_ont_mouse.csv"
+  location_mouse <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/location_ont_mouse.csv"
+
+  process_rat <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/process_ont_rat.csv"
+  myfunction_rat <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/function_ont_rat.csv"
+  location_rat <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/location_ont_rat.csv"
+
+  process_pig <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/process_ont_pig.csv"
+  myfunction_pig <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/function_ont_pig.csv"
+  location_pig <- "C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/location_ont_pig.csv"
+
+  nci <- "https://www.dropbox.com/s/fe8t4nyhbljsn5y/nci.csv?dl=1"
+  human.cell.markers.full <- "https://www.dropbox.com/s/a2tvvuh8kgi340v/human_cell_markers_full_lineage.csv?dl=1"
+  human.cell.markers.short <- "https://www.dropbox.com/s/4njofwfs5uu3wya/human_cell_markers_short_lineage.csv?dl=1"
+  mouse.cell.markers <- "https://www.dropbox.com/s/223bpbc5p24j919/mouse_cell_markers_full_lineage.csv?dl=1"
+  blood.cell.markers.human1 <- "https://www.dropbox.com/s/kl2apjfnbqdw7gj/blood_cell_markers.csv?dl=1"
+  blood.cell.markers.human2 <- "https://www.dropbox.com/s/o28o4fbmmuwtgs3/blood_cell_markers2.csv?dl=1"
+  bone.marrow.cell.markers <- "https://www.dropbox.com/s/gl0vim65cz9804a/bone_marrow_cell_markers.csv?dl=1"
+  tf.targets <- "https://www.dropbox.com/s/cuitt6gzipxaaec/TF%20target%20genes%20gtrd%20v71.csv?dl=1"
+
+  pdt.sig <- "https://www.dropbox.com/s/wr6j8i5gosm959x/pdts_signor.csv?dl=1"
+
+  tf.targets.omnipath <- "https://www.dropbox.com/s/hg3slk150l7zd0x/TF%20all%20targets%20omnipath.csv?dl=1"
+  chromatin <- "https://www.dropbox.com/s/y2gkjn45oxy72nw/chromatin.csv?dl=1"
+  selected <- "https://www.dropbox.com/s/nrraoj8hlvzap87/selected.csv?dl=1"
+  ctams <- "https://www.dropbox.com/s/ev95hm4zz4c535c/ctams.csv?dl=1"
+  kegg <- "https://www.dropbox.com/s/gm2821cmxarv7sx/kegg%20pathways.csv?dl=1"
+  pp.markers.corr.with.cd <- "https://www.dropbox.com/s/aixtdiwhuym9vk6/PP%20Markers%20corr%20with%20CDs.csv?dl=1"
+
+  hallmark.genes <- "https://www.dropbox.com/s/wqvnoalg2v6ufm8/hallmark%20genes%20v71.csv?dl=1"
+
+  cd.phospho.markers <- "https://www.dropbox.com/s/aixtdiwhuym9vk6/PP%20Markers%20corr%20with%20CDs.csv?dl=1"
+  pdts.reactome <- "https://www.dropbox.com/s/rvqjmzg9cq9yjpu/pdts_reactome.csv?dl=1"
+  pdts.process <- "https://www.dropbox.com/s/1vqm9kky5ctzj2g/pdts_process.csv?dl=1"
+  pdts.location <- "https://www.dropbox.com/s/jbroun1ojqu9rnc/pdts_location.csv?dl=1"
+  pdts.nci <- "https://www.dropbox.com/s/qjvmxgp6fd5cv8x/pdts_nci.csv?dl=1"
+
+  ks.omnipath <- "https://www.dropbox.com/s/zdnuxe8anwboks1/Kinase%20substrates%20omnipath.csv?dl=1"
+
+  circuitries <- "https://www.dropbox.com/s/9vykdbcvy0jzh0f/Results%20circuitry%20anal.csv?dl=1"
+
+  ctams.hijazi <- "https://www.dropbox.com/s/zksj57u60q6sg7q/CTAMS_hijazi.csv?dl=1"
+
+
+  dataset.names <- c(
+    "edges", # 1
+    "pdts",
+    "psite",
+    "signor",
+    "ks.omnipath", # 5
+    "reactome",
+    "process",
+    "function",
+    "location",
+    "process_mouse", # 10
+    "function_mouse",
+    "location_mouse",
+    "process_rat",
+    "function_rat",
+    "location_rat", # 15
+    "process_pig",
+    "function_pig",
+    "location_pig",
+    "nci", # 19
+    "human.cell.markers.full", # 20
+    "human.cell.markers.short",
+    "mouse.cell.markers",
+    "blood.cell.markers.human1",
+    "blood.cell.markers.human2",
+    "bone.marrow.cell.markers", # 25
+    "tf.targets",
+    "tf.targets.omnipath",
+    "chromatin",
+    "selected",
+    "ctams", # 30
+    "kegg",
+    "cd.phospho.markers",
+    "pdts.reactome",
+    "pdts.process",
+    "pdts.location", # 35
+    "pdts.nci",
+    "markers.corr.with.cd",
+    "hallmark.genes",
+    "pdt.sig",
+    "circuitries", # 40
+    "ctams.hijazi",
+    "psite_mouse",  # Incorporated new species-specific PhosphoSitePlus data
+    "psite_rat",
+    "psite_human",
+    "psite_rabbit",  # 45
+    "psite_chicken",
+    "psite_cow",
+    "psite_pig",
+    "psite_frog",
+    "psite_dog",  # 50
+    "psite_hamster"
+  )
+
+  datasets <- list(
+    edges, # 1
+    pdts, # 2
+    psite,
+    signor,
+    ks.omnipath, # 5
+    reactome,
+    process,
+    myfunction,
+    location,
+    process_mouse, # 10
+    myfunction_mouse,
+    location_mouse,
+    process_rat,
+    myfunction_rat,
+    location_rat, # 15
+    process_pig,
+    myfunction_pig,
+    location_pig,
+    nci, # 19
+    human.cell.markers.full, # 20
+    human.cell.markers.short,
+    mouse.cell.markers,
+    blood.cell.markers.human1, # 23
+    blood.cell.markers.human2,
+    bone.marrow.cell.markers, # 25
+    tf.targets,
+    tf.targets.omnipath,
+    chromatin, # 28
+    selected,
+    ctams, # 30
+    kegg,
+    cd.phospho.markers,
+    pdts.reactome,
+    pdts.process,
+    pdts.location, # 35
+    pdts.nci,
+    pp.markers.corr.with.cd,
+    hallmark.genes,
+    pdt.sig,
+    circuitries, # 40
+    ctams.hijazi,
+    psite_ks_species$psite_mouse,  # Incorporated new species-specific PhosphoSitePlus data
+    psite_ks_species$psite_rat,
+    psite_ks_species$psite_human,
+    psite_ks_species$psite_rabbit,  # 45
+    psite_ks_species$psite_chicken,
+    psite_ks_species$psite_cow,
+    psite_ks_species$psite_pig,
+    psite_ks_species$psite_frog,
+    psite_ks_species$psite_dog,  # 50
+    psite_ks_species$psite_hamster
+  )
+
+
+  # df.datasets <- list(datasets)
+  names(datasets) <- dataset.names
+  dataset.list <- list()
+  i <- 1
+  for (d in datasets) {
+    names(datasets[1])
+    dataset.list[[i]] <- read.csv(datasets[[i]])
+    names(dataset.list)[i] <- names(datasets[i])
+    i <- i + 1
+  }
+  protein_and_ks_sets <- dataset.list
+  k <- protein_and_ks_sets$process
+  usethis::use_data_raw(name = "protein_and_ks_sets")
+  usethis::use_data(protein_and_ks_sets, overwrite = TRUE)
+}
+
+
+
+uniprot.names <- read.csv("C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/uniprot_reviewed_20230102.csv")
+
+usethis::use_data_raw(name = "uniprot.names")
+usethis::use_data(uniprot.names, overwrite = TRUE)
+
+uniprot.names.mouse <- read.csv("C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/uniprot/uniprot_mouse_reviewed_20230102.csv")
+
+usethis::use_data_raw(name = "uniprot.names.mouse")
+usethis::use_data(uniprot.names.mouse, overwrite = TRUE)
+
+####
+
+
+datasets <- protools::protein_and_ks_sets
+
+d <- datasets$selected
+
+
+j <- 10
+for (d in datasets) {
+  dd <- datasets[j]
+  nn <- names(dd[[1]])
+  ddd <- dd[[1]]
+  names(dd[1])
+  ddd <- subset(ddd, ddd[, 2] > 2)
+  # if (!"genes" %in% nn){
+  i <- 1
+  for (i in 1:nrow(ddd)) {
+    prots <- unique(unlist(strsplit(ddd[i, 3], ";")))
+    genes <- protools::gene.names.from.accessions(prots)
+    ddd$genes[i] <- paste0(genes, collapse = ";")
+  }
+  datasets[[j]] <- ddd
+  # }
+  j <- j + 1
+}
+protein_and_ks_sets <- datasets
+
+usethis::use_data_raw(name = "protein_and_ks_sets")
+usethis::use_data(protein_and_ks_sets, overwrite = TRUE)
+
+
+df.kegg <- read.csv("C:/Users/cutill01/Dropbox/01pedro work/01_data/databases/gene sets/kegg pathways_2.csv")
+i <- 1
+accs <- accessions.from.gene.names(df.kegg$gene)
+df.kegg$proteins <- accs
+
+pathways <- unique(df.kegg$pathway)
+nn <- length(pathways)
+
+pathway <- character(nn)
+genes <- character(nn)
+proteins <- character(nn)
+m <- numeric(nn)
+i <- 1
+for (p in pathways) {
+  xx <- df.kegg[df.kegg$pathway == p, ]
+  genes[i] <- paste0(xx$gene, collapse = ";")
+  proteins[i] <- paste0(xx$proteins, collapse = ";")
+  m[i] <- nrow(xx)
+  i <- i + 1
+}
+
+df.kegg.b <- data.frame(pathways, m, proteins, genes)
+
+df.kegg.b <- df.kegg.b[order(-df.kegg.b$m), ]
+
+protein_and_ks_sets[["kegg"]] <- df.kegg.b
+
+usethis::use_data_raw(name = "protein_and_ks_sets")
+usethis::use_data(protein_and_ks_sets, overwrite = TRUE)
+
+k <- protein_and_ks_sets$kegg$genes[1:10]
+
+
+
+use_package("foreach")
+use_package("doParallel")
+use_package("readxl")
+use_package("dplyr")
+use_package("ggrepel")
+use_package("stringr")
+use_package("ggplot2")
+use_package("ggpubr")
+use_package("ggrepel")
+use_package("igraph")
+use_package("limma")
+document()
+
+# Reload the package: CTRL-L or
+load_all()

data-raw/process files.R

@@ -0,0 +1,51 @@
+# Process species-specific data files
+
+
+# Load packages ----
+library(devtools)
+library(dplyr)
+
+
+# Create species-specific PhosphoSitePlus data ----
+
+# Load PhoshoSitePlus data
+# Available from: https://www.phosphosite.org/staticDownloads
+psite_Kinase_Substrate_Dataset <- read.csv("Kinase_Substrate_Dataset_psite_2023_05.csv")
+
+# Get unique species in dataset
+species_kin <- unique(psite_Kinase_Substrate_Dataset$KIN_ORGANISM)
+species_sub <- unique(psite_Kinase_Substrate_Dataset$SUB_ORGANISM)
+species_list <- dplyr::intersect(species_kin, species_sub)
+
+# Create dataframe in `protools2` required format
+psite_ks_species <- vector("list", length = length(species_list))
+names(psite_ks_species) <- paste0("psite_", species_list)
+for (species in species_list) {
+  psite_ks_species[[paste0("psite_", species)]] <- psite_Kinase_Substrate_Dataset %>%
+    dplyr::filter(KIN_ORGANISM == species & SUB_ORGANISM == species) %>%  # Filters matching species
+    dplyr::group_by(GENE) %>%
+    dplyr::summarise(
+      m = dplyr::n(),
+      subs = paste0(SUB_GENE, "(", SUB_MOD_RSD, ")", collapse = ";")
+    ) %>%
+    dplyr::mutate(
+      organism = species,
+      gene.db = paste0(GENE, ".pSite")
+    ) %>%
+    dplyr::rename(gene = GENE)
+}
+
+# Save the processed data in package (saves to '../data/psite_ks_species.rda')
+usethis::use_data(psite_ks_species)
+
+
+# Combine with previous protein and kinase-substrate sets ----
+
+# Load list object
+load("../data/protein_and_ks_sets.rda")
+
+# Combine lists
+protein_and_ks_sets <- c(protein_and_ks_sets, psite_ks_species)
+
+# Save data in package (saves to '../data/protein_and_ks_sets.rda')
+usethis::use_data(protein_and_ks_sets, overwrite = TRUE)