In this notebook, we download various data files required for the analyses performed in the other notebooks.
Attention
Downloading the TCGA data requires the firehose_get utility, which we assume has been installed and added to the executable
PATH.
import sys
sys.path.append("../lib")
import nbsupport.tcga
import nbsupport.util
firehoseDate = "2014_07_15"
DATA_DIR = "../data"
!mkdir {DATA_DIR}
%cd {DATA_DIR}
/data/s.canisius/notebooks/discover/data
!mkdir downloads
!mkdir entrez
!mkdir tcga
%cd downloads
/data/s.canisius/notebooks/discover/data/downloads
!firehose_get -b -only copynumber_gistic MutSigNozzleReport2CV analyses {firehoseDate} {" ".join(nbsupport.tcga.PANCAN12_STUDIES)}
Validating run selection against Broad Institute website ...
You've asked to download archives for the following tasks
copynumber_gistic MutSigNozzleReport2CV
run against the disease cohorts
COAD LUSC READ GBM LAML HNSC BLCA UCEC LUAD OV BRCA KIRC
from the analyses__2014_07_15 Firehose run.
Attempting to retrieve data for Broad GDAC run analyses__2014_07_15 ...
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--2016-02-24 11:50:45-- http://gdac.broadinstitute.org/runs/analyses__2014_07_15/data/COAD/20140715/gdac.broadinstitute.org_COAD-TP.CopyNumber_Gistic2.Level_4.2014071500.0.0.tar.gz
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--2016-02-24 11:51:12-- http://gdac.broadinstitute.org/runs/analyses__2014_07_15/data/COAD/20140715/gdac.broadinstitute.org_COAD-TP.CopyNumber_Gistic2.Level_4.2014071500.0.0.tar.gz.md5
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--2016-02-24 11:51:12-- http://gdac.broadinstitute.org/runs/analyses__2014_07_15/data/COAD/20140715/gdac.broadinstitute.org_COAD-TP.CopyNumber_Gistic2.aux.2014071500.0.0.tar.gz
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--2016-02-24 11:53:48-- http://gdac.broadinstitute.org/runs/analyses__2014_07_15/data/LUSC/20140715/gdac.broadinstitute.org_LUSC-TP.CopyNumber_Gistic2.Level_4.2014071500.0.0.tar.gz.md5
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--2016-02-24 11:53:49-- http://gdac.broadinstitute.org/runs/analyses__2014_07_15/data/LUSC/20140715/gdac.broadinstitute.org_LUSC-TP.CopyNumber_Gistic2.aux.2014071500.0.0.tar.gz
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55296K ........ ........ ........ ........ ........ ........ 53% 1.91M 40s
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67584K ........ ........ ........ ........ ........ ........ 64% 2.36M 28s
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76800K ........ ........ ........ ........ ........ ........ 73% 2.20M 20s
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18432K ........ ........ ........ ........ ........ ........ 86% 2.54M 1s
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27648K ........ ........ ........ ........ ........ ........ 33% 2.53M 23s
30720K ........ ........ ........ ........ ........ ........ 36% 2.73M 22s
33792K ........ ........ ........ ........ ........ ........ 40% 2.74M 21s
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39936K ........ ........ ........ ........ ........ ........ 47% 2.52M 18s
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55296K ........ ........ ........ ........ ........ ........ 67% 2.74M 11s
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61440K ........ ........ ........ ........ ........ ........ 74% 2.74M 8s
64512K ........ ........ ........ ........ ........ ........ 77% 2.56M 7s
67584K ........ ........ ........ ........ ........ ........ 81% 2.72M 6s
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Now performing post-processing on retrieved files ...
import shutil
import tarfile
import tempfile
from contextlib import closing
for study in nbsupport.tcga.PANCAN12_STUDIES:
filePrefix = "analyses__{date}/{study}/{date2}/gdac.broadinstitute.org_{study}-{tumourType}".format(
date=firehoseDate, date2=firehoseDate.replace("_", ""), study=study, tumourType="TB" if study == "LAML" else "TP")
gisticResults = "{prefix}.CopyNumber_Gistic2.Level_4.{date2}00.0.0.tar.gz".format(
prefix=filePrefix, date2=firehoseDate.replace("_", ""))
with tarfile.open(gisticResults, "r|gz") as archive:
for entry in archive:
if entry.name.endswith("all_thresholded.by_genes.txt"):
with closing(archive.extractfile(entry)) as stream, tempfile.TemporaryFile() as out:
shutil.copyfileobj(stream, out)
out.seek(0)
cn = nbsupport.tcga.read_copynumber_data(out)
cn.to_hdf("../tcga/tcga-pancan12.h5", "/data/{}/cn".format(study), complevel=9, complib="bzip2")
mutsigResults = "{prefix}.MutSigNozzleReport2CV.Level_4.{date2}00.1.0.tar.gz".format(
prefix=filePrefix, date2=firehoseDate.replace("_", ""))
with tarfile.open(mutsigResults, "r|gz") as archive:
for entry in archive:
if entry.name.endswith(".final_analysis_set.maf"):
with closing(archive.extractfile(entry)) as stream, tempfile.TemporaryFile() as out:
shutil.copyfileobj(stream, out)
out.seek(0)
mut = nbsupport.tcga.read_mutation_data(out)
mut.to_hdf("../tcga/tcga-pancan12.h5", "/data/{}/mut".format(study), complevel=9, complib="bzip2")
filePrefix = "analyses__{date}/BRCA/{date2}/gdac.broadinstitute.org_BRCA-TP".format(
date=firehoseDate, date2=firehoseDate.replace("_", ""))
gisticResults = "{prefix}.CopyNumber_Gistic2.Level_4.{date2}00.0.0.tar.gz".format(
prefix=filePrefix, date2=firehoseDate.replace("_", ""))
with tarfile.open(gisticResults, "r|gz") as archive:
for entry in archive:
if entry.name.endswith("amp_genes.conf_99.txt"):
with closing(archive.extractfile(entry)) as stream, open("../tcga/amp_genes.conf_99.BRCA.txt", "w") as out:
shutil.copyfileobj(stream, out)
A list of high-confidence mutational drivers has been published in the following paper.
Tamborero, D. et al. Comprehensive identification of mutational cancer driver genes across 12 tumor types. Sci Rep 3, 2650 (2013), doi:10.1038/srep02650.
import urllib
import zipfile
url = "http://www.nature.com/article-assets/npg/srep/2013/131002/srep02650/extref/srep02650-s2.zip"
filename, response = urllib.urlretrieve(url, "srep02650-s2.zip")
nbsupport.util.check_digest(filename, "5a56134a26ff9e83b40e8cd1e7043e5e")
with zipfile.ZipFile(filename) as zip:
with zip.open("srep02650-s3.csv") as stream, open("../tcga/mutational-drivers.csv", "w") as out:
shutil.copyfileobj(stream, out)
The Bushman lab maintains a list of genes implicated in cancer.
url = "http://www.bushmanlab.org/assets/doc/allonco_20130923.tsv"
filename, respose = urllib.urlretrieve(url, "../tcga/cancer-genes.tsv")
nbsupport.util.check_digest(filename, "72832c847db96c7fb019fa97050fb9a4")
url = "ftp://ftp.ncbi.nlm.nih.gov/genomes/H_sapiens/ARCHIVE/ANNOTATION_RELEASE.105/mapview/seq_gene.md.gz"
filename, respose = urllib.urlretrieve(url, "../entrez/seq_gene.md.gz")
nbsupport.util.check_digest(filename, "6fa4691b852dd9bb603c2a2f64718317")
The following downloads are protected by passwords, and so they cannot be downloaded automatically.
Download the following two files from synapse, and add them to the data/tcga directory.
nbsupport.util.check_digest("../tcga/amp_genes.conf_95.pancan12.txt", "0f23349056bc5d451c2bf8358e99dab8")
nbsupport.util.check_digest("../tcga/del_genes.conf_95.pancan12.txt", "80b3e9027ba6ca0e6b56eedde6bb019f")
Download the following file from MSigDb and add it to the data/msigdb directory.
nbsupport.util.check_digest("../msigdb/c2.cp.v5.0.symbols.gmt", "9790879a470eda3c6c431a91f3b652f8")