+
+
+
+
+
+
+
+More attributes of a Dataframe¶
Pandas is Python package used for data manipulation and analysis. The name is derived from the term "panel data".
+To use pandas, you need to import it. And numpy is required as well.
+It is generally imported using np and pd as abbreviations.
import numpy as np
+import pandas as pd
+population_dict = {'California': 38332521,
+ 'Texas': 26448193,
+ 'New York': 19651127,
+ 'Florida': 19552860,
+ 'Illinois': 12882135}
+population = pd.Series(population_dict)
+print(population)
+population["California":"Texas"]
+California 38332521 +Texas 26448193 +New York 19651127 +Florida 19552860 +Illinois 12882135 +dtype: int64 ++
California 38332521 +Texas 26448193 +dtype: int64+
area_dict = {'California': 423967, 'Texas': 695662, 'New York': 141297,
+ 'Florida': 170312, 'Illinois': 149995}
+area = pd.Series(area_dict)
+
+states = pd.DataFrame({'population': population,
+ 'area': area})
+states
+| + | population | +area | +
|---|---|---|
| California | +38332521 | +423967 | +
| Texas | +26448193 | +695662 | +
| New York | +19651127 | +141297 | +
| Florida | +19552860 | +170312 | +
| Illinois | +12882135 | +149995 | +
print(states.index)
+print(states.columns)
+print(type(states.index))
+print(type(states.columns))
+Index(['California', 'Texas', 'New York', 'Florida', 'Illinois'], dtype='object') +Index(['population', 'area'], dtype='object') +<class 'pandas.core.indexes.base.Index'> +<class 'pandas.core.indexes.base.Index'> ++
In our setting, you are usually going to be importing data from a csv/tsv or an excel. And you chose pandas because the data structure is a bit too complex or it is just an easy way to quickly import it. +In this session, i'll be taking you into a deep dive of the new test directory.
+ +df = pd.read_excel("td_v5.xlsx", sheet_name=None, header=1)
+df.keys()
+dict_keys(['Explanatory note ', 'R&ID indications', 'Neuro STR routing'])+
In the previous command, I'm importing the test directory but i know that the excel has multiple sheets and by default the read_excel cmd will use the first sheet and discard the rest.
+The header option specifies which line is the header.
https://pandas.pydata.org/docs/reference/api/pandas.read_excel.html
+ +df = df["R&ID indications"]
+df.head()
+| + | Clinical indication ID | +Test ID | +Clinical Indication | +Target/Genes | +Test Method | +Commissioning category | +Specialist test group | +Changes since October 2022 v4 publication | +Single national provider | +North East & Yorkshire GLH | +North West GLH | +East GLH | +Central & South GLH | +South West GLH | +North Thames GLH | +South East GLH | +
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | +R67 | +R67.1 | +Monogenic hearing loss | +Hearing loss (126) | +WES or Large Panel | +Specialised | +Audiology | +Update to gene content via PanelApp route | +No | +North West GLH - Manchester University FT | +North West GLH - Manchester University FT | +North West GLH- Manchester University FT | +North Thames GLH - Great Ormond Street FT | +North Thames GLH - Great Ormond Street FT | +North Thames GLH - Great Ormond Street FT | +North Thames GLH - Great Ormond Street FT | +
| 1 | +R67 | +R67.2 | +Monogenic hearing loss | +Hearing loss (126) | +MLPA or equivalent | +Specialised | +Audiology | +No change | +No | +North West GLH - Manchester University FT | +North West GLH - Manchester University FT | +North West GLH- Manchester University FT | +North Thames GLH - Great Ormond Street FT | +North Thames GLH - Great Ormond Street FT | +North Thames GLH - Great Ormond Street FT | +North Thames GLH - Great Ormond Street FT | +
| 2 | +R125 | +R125.1 | +Thoracic aortic aneurysm or dissection | +Thoracic aortic aneurysm or dissection (700) | +WES or Medium Panel | +Specialised | +Cardiology | +Update to gene content via PanelApp route | +No | +North West GLH - Manchester University FT | +North West GLH - Manchester University FT | +South West GLH - North Bristol Trust | +Central and South GLH - Salisbury FT | +South West GLH - North Bristol Trust | +South East GLH - Royal Brompton and Harefield FT | +South East GLH - Royal Brompton and Harefield FT | +
| 3 | +R125 | +R125.2 | +Thoracic aortic aneurysm or dissection | +Thoracic aortic aneurysm or dissection (700) | +MLPA or equivalent | +Specialised | +Cardiology | +No change | +No | +North West GLH - Manchester University FT | +North West GLH - Manchester University FT | +South West GLH - North Bristol Trust | +Central and South GLH - Salisbury FT | +South West GLH - North Bristol Trust | +South East GLH - Royal Brompton and Harefield FT | +South East GLH - Royal Brompton and Harefield FT | +
| 4 | +R127 | +R127.1 | +Long QT syndrome | +Long QT syndrome (76) | +Small panel | +Specialised | +Cardiology | +No change | +No | +North West GLH - Manchester University FT | +North West GLH - Manchester University FT | +South West GLH - North Bristol Trust | +Central and South GLH - Oxford University FT | +South West GLH - North Bristol Trust | +South East GLH - Royal Brompton and Harefield FT | +South East GLH - Royal Brompton and Harefield FT | +
We can safely remove columns after the Changes since October 2022 v4 publication column.
df.drop(df.columns[8:], axis=1, inplace=True)
+df.head()
+| + | Clinical indication ID | +Test ID | +Clinical Indication | +Target/Genes | +Test Method | +Commissioning category | +Specialist test group | +Changes since October 2022 v4 publication | +
|---|---|---|---|---|---|---|---|---|
| 0 | +R67 | +R67.1 | +Monogenic hearing loss | +Hearing loss (126) | +WES or Large Panel | +Specialised | +Audiology | +Update to gene content via PanelApp route | +
| 1 | +R67 | +R67.2 | +Monogenic hearing loss | +Hearing loss (126) | +MLPA or equivalent | +Specialised | +Audiology | +No change | +
| 2 | +R125 | +R125.1 | +Thoracic aortic aneurysm or dissection | +Thoracic aortic aneurysm or dissection (700) | +WES or Medium Panel | +Specialised | +Cardiology | +Update to gene content via PanelApp route | +
| 3 | +R125 | +R125.2 | +Thoracic aortic aneurysm or dissection | +Thoracic aortic aneurysm or dissection (700) | +MLPA or equivalent | +Specialised | +Cardiology | +No change | +
| 4 | +R127 | +R127.1 | +Long QT syndrome | +Long QT syndrome (76) | +Small panel | +Specialised | +Cardiology | +No change | +
Let's say that we want to get all the clinical indications that had changes i.e. remove the lines with the No change.
df_with_changes = df[df["Changes since October 2022 v4 publication"].str.contains("No change")==False]
+df_with_changes.head()
+| + | Clinical indication ID | +Test ID | +Clinical Indication | +Target/Genes | +Test Method | +Commissioning category | +Specialist test group | +Changes since October 2022 v4 publication | +
|---|---|---|---|---|---|---|---|---|
| 0 | +R67 | +R67.1 | +Monogenic hearing loss | +Hearing loss (126) | +WES or Large Panel | +Specialised | +Audiology | +Update to gene content via PanelApp route | +
| 2 | +R125 | +R125.1 | +Thoracic aortic aneurysm or dissection | +Thoracic aortic aneurysm or dissection (700) | +WES or Medium Panel | +Specialised | +Cardiology | +Update to gene content via PanelApp route | +
| 8 | +R129 | +R129.1 | +Catecholaminergic polymorphic VT | +Catecholaminergic polymorphic VT (214) | +Small panel | +Specialised | +Cardiology | +Update to gene content via PanelApp route | +
| 12 | +R131 | +R131.1 | +Hypertrophic cardiomyopathy | +Hypertrophic cardiomyopathy - teen and adult (49) | +WES or Medium Panel | +Specialised | +Cardiology | +Update to gene content via PanelApp route | +
| 18 | +R135 | +R135.2 | +Paediatric or syndromic cardiomyopathy | +Cardiomyopathies - including childhood onset (... | +WGS | +Specialised | +Cardiology | +Update to gene content via PanelApp route | +
Let's break down the command line:
+ +df["Changes since October 2022 v4 publication"].head()
+0 Update to gene content via PanelApp route +1 No change +2 Update to gene content via PanelApp route +3 No change +4 No change +Name: Changes since October 2022 v4 publication, dtype: object+
type(df["Changes since October 2022 v4 publication"])
+pandas.core.series.Series+
df["Changes since October 2022 v4 publication"].str.contains("No change")
+0 False +1 True +2 False +3 True +4 True + ... +623 True +624 True +625 False +626 True +627 False +Name: Changes since October 2022 v4 publication, Length: 628, dtype: bool+
df_with_changes.shape
+(127, 8)+
Now we have all the clinical indications that are going to require some work. We can see what type of work by looking at the same column.
+ +df_with_changes["Changes since October 2022 v4 publication"].unique()
+array(['Update to gene content via PanelApp route', + 'Addition of semi-rapid testing pathway for WGS indications', + 'Test type reinstated', + 'New clinical indication added, panel line', + 'New clinical indication added, CNV line', 'Removed STR line', + 'Added Confirmatory STR testing ', 'Gene target addition', + 'New Clinical Indication added', + 'Addition of Semi-rapid testing pathway for WGS indications', + 'New clinical indication added', + 'POT1 gene target added, moved to small panel ', + 'POT1 gene target added', 'New test type added ', + 'Test type added for deep sequencing', + 'Removed STR line as STR to be analysed off of WGS', + 'Removed STR line as STRs to be analysed off of WGS', + 'RFC1 STR added', 'no change ', + 'Update to gene content via PanelApp route, Changed CI name', + 'Addition of semi-rapid testing pathway for WGS indications '], + dtype=object)+
df_with_changes["Changes since October 2022 v4 publication"].unique().shape
+(21,)+
21 "different" types of changes. It's still quite a lot.
+We can trim it down by filtering on the test method.
+ +filtering_string = [
+ "Medium panel", "Single gene sequencing <=10 amplicons",
+ "Single gene sequencing <10 amplicons",
+ "Single gene sequencing >=10 amplicons",
+ "Single gene testing (<10 amplicons)", "small panel", "Small panel",
+ "Small panel - deep sequencing", "WES or Large panel", "WES or Large Panel",
+ "WES or Large penel", "WES or Medium panel", "WES or Medium Panel",
+ "WES or Small Panel", "WGS"
+]
+
+df_test_method_filtered = df_with_changes[df_with_changes["Test Method"].str.contains("|".join(filtering_string))]
+print(df_test_method_filtered["Changes since October 2022 v4 publication"].unique().shape)
+df_test_method_filtered
+(7,) ++
/tmp/ipykernel_27596/2676225020.py:11: UserWarning: This pattern is interpreted as a regular expression, and has match groups. To actually get the groups, use str.extract.
+ df_test_method_filtered = df_with_changes[df_with_changes["Test Method"].str.contains("|".join(filtering_string))]
+
+| + | Clinical indication ID | +Test ID | +Clinical Indication | +Target/Genes | +Test Method | +Commissioning category | +Specialist test group | +Changes since October 2022 v4 publication | +
|---|---|---|---|---|---|---|---|---|
| 0 | +R67 | +R67.1 | +Monogenic hearing loss | +Hearing loss (126) | +WES or Large Panel | +Specialised | +Audiology | +Update to gene content via PanelApp route | +
| 2 | +R125 | +R125.1 | +Thoracic aortic aneurysm or dissection | +Thoracic aortic aneurysm or dissection (700) | +WES or Medium Panel | +Specialised | +Cardiology | +Update to gene content via PanelApp route | +
| 8 | +R129 | +R129.1 | +Catecholaminergic polymorphic VT | +Catecholaminergic polymorphic VT (214) | +Small panel | +Specialised | +Cardiology | +Update to gene content via PanelApp route | +
| 12 | +R131 | +R131.1 | +Hypertrophic cardiomyopathy | +Hypertrophic cardiomyopathy - teen and adult (49) | +WES or Medium Panel | +Specialised | +Cardiology | +Update to gene content via PanelApp route | +
| 18 | +R135 | +R135.2 | +Paediatric or syndromic cardiomyopathy | +Cardiomyopathies - including childhood onset (... | +WGS | +Specialised | +Cardiology | +Update to gene content via PanelApp route | +
| ... | +... | +... | +... | +... | +... | +... | +... | +... | +
| 595 | +R139 | +R139.1 | +Laterality disorders and isomerism | +Laterality disorders and isomerism (549) | +WES or Medium Panel | +Specialised | +Respiratory | +Update to gene content via PanelApp route | +
| 601 | +R189 | +R189.1 | +Respiratory ciliopathies including non-CF bron... | +Respiratory ciliopathies including non-CF bron... | +WES or Medium Panel | +Specialised | +Respiratory | +Update to gene content via PanelApp route | +
| 613 | +R434 | +R434.1 | +Recurrent episodic apnoea | +Recurrent episodic apnoea (1219) | +Small panel | +Specialised | +Respiratory | +New clinical indication added | +
| 625 | +R412 | +R412.1 | +Fetal anomalies with a likely genetic cause - ... | +Fetal anomalies (478) | +WES or Large Panel | +Specialised | +Specialised | +Update to gene content via PanelApp route | +
| 627 | +R441 | +R441.1 | +Unexplained death in infancy and sudden unexp... | +Unexplained death in infancy and sudden unexpl... | +WGS | +Specialised | +Specialised | +New clinical indication added | +
86 rows × 8 columns
+One thing I'm interested in is if the targets for the clinical indications are panelapp panels or single genes. +Let's check that out.
+ +df_test_method_filtered[df_test_method_filtered["Target/Genes"].str.contains("\(")==False]
+| + | Clinical indication ID | +Test ID | +Clinical Indication | +Target/Genes | +Test Method | +Commissioning category | +Specialist test group | +Changes since October 2022 v4 publication | +
|---|---|---|---|---|---|---|---|---|
| 86 | +R430 | +R430.1 | +Inherited prostate cancer | +BRCA1, BRCA2, MLH1, MSH2, MSH6, ATM, PALB2, CH... | +Small panel | +Core | +Core | +New clinical indication added, panel line | +
| 158 | +R144 | +R144.1 | +Congenital hyperinsulinism | +ABCC8;KCNJ11 | +Small panel | +Highly Specialised | +Endocrinology | +Update to gene content via PanelApp route | +
| 216 | +R440 | +R440.1 | +Hereditary isolated diabetes insipidus | +AVP; AVPR2; AQP2 | +Small panel | +Specialised | +Endocrinology | +New clinical indication added, panel line | +
| 286 | +R92 | +R92.2 | +Rare anaemia | +HBA1; HBA2; HBG1; HBG2; HBB | +Small panel | +Specialised | +Haematology | +Update to gene content via PanelApp route | +
| 322 | +R216 | +R216.1 | +Li Fraumeni Syndrome | +TP53; POT1 | +Small panel | +Specialised | +Inherited cancer | +POT1 gene target added, moved to small panel | +
| 455 | +R228 | +R228.3 | +Tuberous sclerosis | +TSC1;TSC2 | +Small panel - deep sequencing | +Specialised | +Neurology | +Test type added for deep sequencing | +
These genes will need to be checked. +Let's extract them.
+ +df_single_genes = df_test_method_filtered[df_test_method_filtered["Target/Genes"].str.contains("\(")==False]
+df_single_genes.loc[:, "Target/Genes"].iloc[0]
+'BRCA1, BRCA2, MLH1, MSH2, MSH6, ATM, PALB2, CHEK2\xa0'+
Looks like the encoding of the excel file is wrong. Let's fix that.
+ +df_normalized = df_test_method_filtered.apply(lambda x: x.str.normalize("NFKD").str.strip())
+df_single_genes = df_normalized[df_normalized["Target/Genes"].str.contains("\(")==False]
+df_single_genes.loc[:, "Target/Genes"].iloc[0]
+'BRCA1, BRCA2, MLH1, MSH2, MSH6, ATM, PALB2, CHEK2'+
I also need to look at the panelapp panels and their content to see if any work on the panel database is necessary.
+ +import regex
+
+df_panels = df_normalized[df_normalized["Target/Genes"].str.contains("\(")==True]
+
+panelapp_panel_ids = []
+
+for panel in df_panels["Target/Genes"]:
+ match = regex.search(r"[0-9]+", panel)
+ panelapp_panel_ids.append(match.group(0))
+
+panelapp_panel_ids
+['126', + '700', + '214', + '49', + '749', + '478', + '486', + '285', + '490', + '553', + '555', + '77', + '565', + '293', + '473', + '650', + '130', + '546', + '483', + '514', + '1217', + '508', + '508', + '525', + '157', + '519', + '518', + '398', + '526', + '528', + '529', + '467', + '533', + '534', + '535', + '536', + '537', + '538', + '539', + '168', + '196', + '309', + '269', + '496', + '147', + '465', + '466', + '488', + '540', + '847', + '474', + '402', + '567', + '568', + '579', + '22', + '207', + '225', + '258', + '488', + '78', + '179', + '491', + '162', + '230', + '307', + '509', + '186', + '3', + '487', + '106', + '292', + '548', + '149', + '678', + '549', + '550', + '1219', + '478', + '749']+
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html
+ +| \n", + " | population | \n", + "area | \n", + "
|---|---|---|
| California | \n", + "38332521 | \n", + "423967 | \n", + "
| Texas | \n", + "26448193 | \n", + "695662 | \n", + "
| New York | \n", + "19651127 | \n", + "141297 | \n", + "
| Florida | \n", + "19552860 | \n", + "170312 | \n", + "
| Illinois | \n", + "12882135 | \n", + "149995 | \n", + "
| \n", + " | Clinical indication ID | \n", + "Test ID | \n", + "Clinical Indication | \n", + "Target/Genes | \n", + "Test Method | \n", + "Commissioning category | \n", + "Specialist test group | \n", + "Changes since October 2022 v4 publication | \n", + "Single national provider | \n", + "North East & Yorkshire GLH | \n", + "North West GLH | \n", + "East GLH | \n", + "Central & South GLH | \n", + "South West GLH | \n", + "North Thames GLH | \n", + "South East GLH | \n", + "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "R67 | \n", + "R67.1 | \n", + "Monogenic hearing loss | \n", + "Hearing loss (126) | \n", + "WES or Large Panel | \n", + "Specialised | \n", + "Audiology | \n", + "Update to gene content via PanelApp route | \n", + "No | \n", + "North West GLH - Manchester University FT | \n", + "North West GLH - Manchester University FT | \n", + "North West GLH- Manchester University FT | \n", + "North Thames GLH - Great Ormond Street FT | \n", + "North Thames GLH - Great Ormond Street FT | \n", + "North Thames GLH - Great Ormond Street FT | \n", + "North Thames GLH - Great Ormond Street FT | \n", + "
| 1 | \n", + "R67 | \n", + "R67.2 | \n", + "Monogenic hearing loss | \n", + "Hearing loss (126) | \n", + "MLPA or equivalent | \n", + "Specialised | \n", + "Audiology | \n", + "No change | \n", + "No | \n", + "North West GLH - Manchester University FT | \n", + "North West GLH - Manchester University FT | \n", + "North West GLH- Manchester University FT | \n", + "North Thames GLH - Great Ormond Street FT | \n", + "North Thames GLH - Great Ormond Street FT | \n", + "North Thames GLH - Great Ormond Street FT | \n", + "North Thames GLH - Great Ormond Street FT | \n", + "
| 2 | \n", + "R125 | \n", + "R125.1 | \n", + "Thoracic aortic aneurysm or dissection | \n", + "Thoracic aortic aneurysm or dissection (700) | \n", + "WES or Medium Panel | \n", + "Specialised | \n", + "Cardiology | \n", + "Update to gene content via PanelApp route | \n", + "No | \n", + "North West GLH - Manchester University FT | \n", + "North West GLH - Manchester University FT | \n", + "South West GLH - North Bristol Trust | \n", + "Central and South GLH - Salisbury FT | \n", + "South West GLH - North Bristol Trust | \n", + "South East GLH - Royal Brompton and Harefield FT | \n", + "South East GLH - Royal Brompton and Harefield FT | \n", + "
| 3 | \n", + "R125 | \n", + "R125.2 | \n", + "Thoracic aortic aneurysm or dissection | \n", + "Thoracic aortic aneurysm or dissection (700) | \n", + "MLPA or equivalent | \n", + "Specialised | \n", + "Cardiology | \n", + "No change | \n", + "No | \n", + "North West GLH - Manchester University FT | \n", + "North West GLH - Manchester University FT | \n", + "South West GLH - North Bristol Trust | \n", + "Central and South GLH - Salisbury FT | \n", + "South West GLH - North Bristol Trust | \n", + "South East GLH - Royal Brompton and Harefield FT | \n", + "South East GLH - Royal Brompton and Harefield FT | \n", + "
| 4 | \n", + "R127 | \n", + "R127.1 | \n", + "Long QT syndrome | \n", + "Long QT syndrome (76) | \n", + "Small panel | \n", + "Specialised | \n", + "Cardiology | \n", + "No change | \n", + "No | \n", + "North West GLH - Manchester University FT | \n", + "North West GLH - Manchester University FT | \n", + "South West GLH - North Bristol Trust | \n", + "Central and South GLH - Oxford University FT | \n", + "South West GLH - North Bristol Trust | \n", + "South East GLH - Royal Brompton and Harefield FT | \n", + "South East GLH - Royal Brompton and Harefield FT | \n", + "
| \n", + " | Clinical indication ID | \n", + "Test ID | \n", + "Clinical Indication | \n", + "Target/Genes | \n", + "Test Method | \n", + "Commissioning category | \n", + "Specialist test group | \n", + "Changes since October 2022 v4 publication | \n", + "
|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "R67 | \n", + "R67.1 | \n", + "Monogenic hearing loss | \n", + "Hearing loss (126) | \n", + "WES or Large Panel | \n", + "Specialised | \n", + "Audiology | \n", + "Update to gene content via PanelApp route | \n", + "
| 1 | \n", + "R67 | \n", + "R67.2 | \n", + "Monogenic hearing loss | \n", + "Hearing loss (126) | \n", + "MLPA or equivalent | \n", + "Specialised | \n", + "Audiology | \n", + "No change | \n", + "
| 2 | \n", + "R125 | \n", + "R125.1 | \n", + "Thoracic aortic aneurysm or dissection | \n", + "Thoracic aortic aneurysm or dissection (700) | \n", + "WES or Medium Panel | \n", + "Specialised | \n", + "Cardiology | \n", + "Update to gene content via PanelApp route | \n", + "
| 3 | \n", + "R125 | \n", + "R125.2 | \n", + "Thoracic aortic aneurysm or dissection | \n", + "Thoracic aortic aneurysm or dissection (700) | \n", + "MLPA or equivalent | \n", + "Specialised | \n", + "Cardiology | \n", + "No change | \n", + "
| 4 | \n", + "R127 | \n", + "R127.1 | \n", + "Long QT syndrome | \n", + "Long QT syndrome (76) | \n", + "Small panel | \n", + "Specialised | \n", + "Cardiology | \n", + "No change | \n", + "
| \n", + " | Clinical indication ID | \n", + "Test ID | \n", + "Clinical Indication | \n", + "Target/Genes | \n", + "Test Method | \n", + "Commissioning category | \n", + "Specialist test group | \n", + "Changes since October 2022 v4 publication | \n", + "
|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "R67 | \n", + "R67.1 | \n", + "Monogenic hearing loss | \n", + "Hearing loss (126) | \n", + "WES or Large Panel | \n", + "Specialised | \n", + "Audiology | \n", + "Update to gene content via PanelApp route | \n", + "
| 2 | \n", + "R125 | \n", + "R125.1 | \n", + "Thoracic aortic aneurysm or dissection | \n", + "Thoracic aortic aneurysm or dissection (700) | \n", + "WES or Medium Panel | \n", + "Specialised | \n", + "Cardiology | \n", + "Update to gene content via PanelApp route | \n", + "
| 8 | \n", + "R129 | \n", + "R129.1 | \n", + "Catecholaminergic polymorphic VT | \n", + "Catecholaminergic polymorphic VT (214) | \n", + "Small panel | \n", + "Specialised | \n", + "Cardiology | \n", + "Update to gene content via PanelApp route | \n", + "
| 12 | \n", + "R131 | \n", + "R131.1 | \n", + "Hypertrophic cardiomyopathy | \n", + "Hypertrophic cardiomyopathy - teen and adult (49) | \n", + "WES or Medium Panel | \n", + "Specialised | \n", + "Cardiology | \n", + "Update to gene content via PanelApp route | \n", + "
| 18 | \n", + "R135 | \n", + "R135.2 | \n", + "Paediatric or syndromic cardiomyopathy | \n", + "Cardiomyopathies - including childhood onset (... | \n", + "WGS | \n", + "Specialised | \n", + "Cardiology | \n", + "Update to gene content via PanelApp route | \n", + "
| \n", + " | Clinical indication ID | \n", + "Test ID | \n", + "Clinical Indication | \n", + "Target/Genes | \n", + "Test Method | \n", + "Commissioning category | \n", + "Specialist test group | \n", + "Changes since October 2022 v4 publication | \n", + "
|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "R67 | \n", + "R67.1 | \n", + "Monogenic hearing loss | \n", + "Hearing loss (126) | \n", + "WES or Large Panel | \n", + "Specialised | \n", + "Audiology | \n", + "Update to gene content via PanelApp route | \n", + "
| 2 | \n", + "R125 | \n", + "R125.1 | \n", + "Thoracic aortic aneurysm or dissection | \n", + "Thoracic aortic aneurysm or dissection (700) | \n", + "WES or Medium Panel | \n", + "Specialised | \n", + "Cardiology | \n", + "Update to gene content via PanelApp route | \n", + "
| 8 | \n", + "R129 | \n", + "R129.1 | \n", + "Catecholaminergic polymorphic VT | \n", + "Catecholaminergic polymorphic VT (214) | \n", + "Small panel | \n", + "Specialised | \n", + "Cardiology | \n", + "Update to gene content via PanelApp route | \n", + "
| 12 | \n", + "R131 | \n", + "R131.1 | \n", + "Hypertrophic cardiomyopathy | \n", + "Hypertrophic cardiomyopathy - teen and adult (49) | \n", + "WES or Medium Panel | \n", + "Specialised | \n", + "Cardiology | \n", + "Update to gene content via PanelApp route | \n", + "
| 18 | \n", + "R135 | \n", + "R135.2 | \n", + "Paediatric or syndromic cardiomyopathy | \n", + "Cardiomyopathies - including childhood onset (... | \n", + "WGS | \n", + "Specialised | \n", + "Cardiology | \n", + "Update to gene content via PanelApp route | \n", + "
| ... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "
| 595 | \n", + "R139 | \n", + "R139.1 | \n", + "Laterality disorders and isomerism | \n", + "Laterality disorders and isomerism (549) | \n", + "WES or Medium Panel | \n", + "Specialised | \n", + "Respiratory | \n", + "Update to gene content via PanelApp route | \n", + "
| 601 | \n", + "R189 | \n", + "R189.1 | \n", + "Respiratory ciliopathies including non-CF bron... | \n", + "Respiratory ciliopathies including non-CF bron... | \n", + "WES or Medium Panel | \n", + "Specialised | \n", + "Respiratory | \n", + "Update to gene content via PanelApp route | \n", + "
| 613 | \n", + "R434 | \n", + "R434.1 | \n", + "Recurrent episodic apnoea | \n", + "Recurrent episodic apnoea (1219) | \n", + "Small panel | \n", + "Specialised | \n", + "Respiratory | \n", + "New clinical indication added | \n", + "
| 625 | \n", + "R412 | \n", + "R412.1 | \n", + "Fetal anomalies with a likely genetic cause - ... | \n", + "Fetal anomalies (478) | \n", + "WES or Large Panel | \n", + "Specialised | \n", + "Specialised | \n", + "Update to gene content via PanelApp route | \n", + "
| 627 | \n", + "R441 | \n", + "R441.1 | \n", + "Unexplained death in infancy and sudden unexp... | \n", + "Unexplained death in infancy and sudden unexpl... | \n", + "WGS | \n", + "Specialised | \n", + "Specialised | \n", + "New clinical indication added | \n", + "
86 rows × 8 columns
\n", + "| \n", + " | Clinical indication ID | \n", + "Clinical Indication | \n", + "Target/Genes | \n", + "
|---|---|---|---|
| 158 | \n", + "R144 | \n", + "Congenital hyperinsulinism | \n", + "ABCC8;KCNJ11 | \n", + "