There is a newer version of the record available.

Published January 29, 2020 | Version 0.2.1
Dataset Open

Pan-cancer Aberrant Pathway Activity Analysis (PAPAA)

  • 1. CLEVELAND CLINIC

Description

Information about the dataset files:

1) pancan_rnaseq_freeze.tsv.gz: Publicly available gene expression data for the TCGA Pan-cancer dataset. File: PanCanAtlas EBPlusPlusAdjustPANCAN_IlluminaHiSeq_RNASeqV2.geneExp.tsv was processed using script process_sample_freeze.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [http://api.gdc.cancer.gov/data/3586c0da-64d0-4b74-a449-5ff4d9136611] [https://doi.org/10.1016/j.celrep.2018.03.046]

2) pancan_mutation_freeze.tsv.gz: Publicly available Mutational information for TCGA Pan-cancer dataset.  File: mc3.v0.2.8.PUBLIC.maf.gz was processed using script process_sample_freeze.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [http://api.gdc.cancer.gov/data/1c8cfe5f-e52d-41ba-94da-f15ea1337efc] [https://doi.org/10.1016/j.celrep.2018.03.046] 

3) pancan_GISTIC_threshold.tsv.gz: Publicly available Gene- level copy number information of the TCGA Pan-cancer dataset. This file is processed using script process_copynumber.py  by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. The files copy_number_loss_status.tsv.gz and copy_number_gain_status.tsv.gz generated from this data are used as inputs in our Galaxy pipeline. [https://xenabrowser.net/datapages/?cohort=TCGA%20Pan-Cancer%20(PANCAN)&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443] [https://doi.org/10.1016/j.celrep.2018.03.046]

4) mutation_burden_freeze.tsv.gz: Publicly available Mutational information for TCGA Pan-cancer dataset  mc3.v0.2.8.PUBLIC.maf.gz was processed using script process_sample_freeze.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [https://github.com/greenelab/pancancer/][http://api.gdc.cancer.gov/data/1c8cfe5f-e52d-41ba-94da-f15ea1337efc] [https://doi.org/10.1016/j.celrep.2018.03.046]

5) sample_freeze.tsv or sample_freeze_version4_modify.tsv: The file lists the frozen samples as determined by TCGA PanCancer Atlas consortium along with raw RNAseq and mutation data. These were previously determined and included for all downstream analysis All other datasets were processed and subset according to the frozen samples.[https://github.com/greenelab/pancancer/]

6) vogelstein_cancergenes.tsv: compendium of OG and TSG used for the analysis. [https://github.com/greenelab/pancancer/]

7) CCLE_DepMap_18Q1_maf_20180207.txt.gz Publicly available Mutational data for CCLE cell lines from Broad Institute Cancer Cell Line Encyclopedia (CCLE) / DepMap Portal. [https://depmap.org/portal/download/api/download/external?file_name=ccle%2FCCLE_DepMap_18Q1_maf_20180207.txt]

8) ccle_rnaseq_genes_rpkm_20180929_mod.gct.gz: Publicly available Expression data for 1019 cell lines (RPKM) from  Broad Institute Cancer Cell Line Encyclopedia (CCLE) / DepMap Portal. [https://depmap.org/portal/download/api/download/external?file_name=ccle%2Fccle_2019%2FCCLE_RNAseq_genes_rpkm_20180929.gct.gz]

9) CCLE_MUT_CNA_AMP_DEL_binary_Revealer.gct: Publicly available merged Mutational and copy number alterations that include gene amplifications and deletions for the CCLE cell lines. This data is represented in the binary format and provided by the Broad Institute Cancer Cell Line Encyclopedia (CCLE) / DepMap Portal. [https://data.broadinstitute.org/ccle_legacy_data/binary_calls_for_copy_number_and_mutation_data/CCLE_MUT_CNA_AMP_DEL_binary_Revealer.gct]

10) GDSC_cell_lines_EXP_CCLE_names.csv.gz Publicly available RMA normalized expression data for Genomics of Drug Sensitivity in Cancer(GDSC) cell-lines. File gdsc_cell_line_RMA_proc_basalExp.csv was downloaded. This data was subsetted to 389 cell lines that are common among CCLE and GDSC. All the GDSC cell line names were replaced with CCLE cell line names for further processing. [https://www.cancerrxgene.org/gdsc1000/GDSC1000_WebResources//Data/preprocessed/Cell_line_RMA_proc_basalExp.txt.zip]

11) GDSC_CCLE_common_mut_cnv_binary.csv.gz:   A subset of merged Mutational and copy number alterations that include gene amplifications and deletions for common cell lines between GDSC and CCLE. This file is generated using CCLE_MUT_CNA_AMP_DEL_binary_Revealer.gct and a list of common cell lines. 

12) gdsc1_ccle_pharm_fitted_dose_data.txt.gz: Pharmacological data for GDSC1 cell lines. [ftp://ftp.sanger.ac.uk/pub/project/cancerrxgene/releases/current_release/GDSC1_fitted_dose_response_15Oct19.xlsx]

13) gdsc2_ccle_pharm_fitted_dose_data.txt.gz: Pharmacological data for GDSC2 cell lines. [ftp://ftp.sanger.ac.uk/pub/project/cancerrxgene/releases/current_release/GDSC2_fitted_dose_response_15Oct19.xlsx]

14) compounds.csv: list of pharmacological compounds tested for our analysis

15) tcga_dictonary.tsv: list of cancer types used in the analysis. 

16) seg_based_scores.tsv: Measurement of total copy number burden, Percent of genome altered by copy number alterations. This file was used as part of the Pancancer analysis by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [https://github.com/greenelab/pancancer/]

17) sign.csv: file with original values assigned for tumor [1] or normal [-1]  for given external samples (GSE69822)

18) vlog_trans.csv: variant stabilized log transformed expression values for given external samples (GSE69822)

19 path_genes.csv: file with list of ERK/RAS/PI3K pathway genes used in the analysis. 

Files

compounds.csv

Files (3.5 GB)

Name Size Download all
md5:01e2f480fa808ca9ab95e014b1594e62
62.0 MB Download
md5:b1f7e5997d0a6baca276878907616b1e
3.0 MB Download
md5:f8276ed5f0fc0e76b50934b9a5e7f04a
126.1 MB Download
md5:82057eceab3bfd24fbf3a0106eee86d2
926 Bytes Preview Download
md5:318751aa7162d2a345ebf9ea62449aa3
903.3 kB Download
md5:96a8ac9339e5dab633c899adf767fe0a
802.8 kB Download
md5:02e72c33071307ff6570621480d3c90b
1.9 GB Download
md5:e4687066af79b86f08228368b5752eec
4.0 MB Download
md5:39511d74034b932f7b7697dc00b0e6a1
1.4 MB Download
md5:8d8a506c722dc68694b4f0483e38e582
1.2 MB Download
md5:0d615fc034fd86cef51c72d324f3ebdb
26.1 MB Download
md5:6c7f98e84f3823186674545df4cacdaf
707.9 MB Download
md5:086a865f3ce79fffcb732165cb552a10
312.5 kB Download
md5:045c0b9f434e1e0d932e4477145feb84
43.0 MB Download
md5:e3e4baebfb732d455eb61b2ce01174bb
3.5 MB Download
md5:c56f6a26fe154cf970bfed53a3cedd0a
655.1 MB Download
md5:12806d2cbcc21c244a4e06f10201135b
235 Bytes Preview Download
md5:ce9f8d12eaf2d696974440371096d4f4
454.8 kB Download
md5:9997626e6e0e3632d7d0b39c66618eae
413.1 kB Preview Download
md5:24ad6e2c29beb206ca068828ec99da74
454.7 kB Download
md5:fcf3c09d769fc1bc8758974efce0b10c
30 Bytes Preview Download
md5:794575895312e3d92d1b4b739a2e6760
975 Bytes Download
md5:0cf1d5c037a1ecbb5caa5883387b08db
13.3 MB Preview Download
md5:e2486e5fe3b28c69e5237601feb48503
14.3 kB Download

Additional details

References

  • Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas Way G.P., Sanchez-Vega F., La K., Armenia J., Chatila W.K., Luna A., Sander C., (...), The Cancer Genome Atlas Research Network (2018) Cell Reports, 23 (1) , pp. 172-180.e3.
  • Oncogenic Signaling Pathways in The Cancer Genome Atlas Sanchez-Vega F., Mina M., Armenia J., Chatila W.K., Luna A., La K.C., Dimitriadoy S., (...), The Cancer Genome Atlas Research Network (2018) Cell, 173 (2) , pp. 321-337.e10.
  • The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity Barretina Caponigro Stransky et al. Nature doi:10.1038/nature11003 / Mar 29, 2012
  • Next-generation characterization of the Cancer Cell Line Encyclopedia Ghandi, M., Huang F. et al. Nature doi:10.1038/s41586-019-1186-3 / May 8, 2019
  • Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells. Yang et al., (2013) Nucl. Acids Res. 41 (Database issue): D955 - D961. (PMID:23180760 )
  • A landscape of pharmacogenomic interactions in cancer Iorio et al., (2016). Cell, Volume 166, Issue 3, 740 - 754 (PMID:27397505 )
  • Systematic identification of genomic markers of drug sensitivity in cancer cells Garnett et al., (2012) Nature volume 483, pages 570 – 575 (PMID:27397505 )
  • Mermel, C.H., Schumacher, S.E., Hill, B. et al. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol 12, R41 (2011). https://doi.org/10.1186/gb-2011-12-4-r41
  • Kiselev VY, Juvin V, Malek M, Luscombe N et al. Perturbations of PIP3 signalling trigger a global remodelling of mRNA landscape and reveal a transcriptional feedback loop. Nucleic Acids Res 2015 Nov 16;43(20):9663-79. PMID: 26464442