10.5281/zenodo.1494861
https://zenodo.org/records/1494861
oai:zenodo.org:1494861
Kuijjer, Marieke Lydia
Marieke Lydia
Kuijjer
0000-0001-6280-3130
Centre for Molecular Medicine Norway, University of Oslo
Gene and pathway mutation scores for 5,805 primary tumors from TCGA
Zenodo
2018
somatic mutations
mutations
SAMBAR
de-sparsification
cancer
TCGA
mutation data
mutation scores
pathway mutation scores
biological pathways
gene mutation scores
subtypes
cancer subtypes
pan-cancer
Paulson, Joseph Nathaniel
Joseph Nathaniel
Paulson
0000-0001-8221-7139
Genentech Inc.
Salzman, Peter
Peter
Salzman
Bristol-Myers Squibb
Ding, Wei
Wei
Ding
University of Massachusetts Boston
Quackenbush, John
John
Quackenbush
0000-0002-2702-5879
Harvard TH Chan School of Public Health
2018-11-23
10.1038/s41416-018-0109-7
10.5281/zenodo.1494839
https://zenodo.org/communities/mkuijjer
Creative Commons Attribution 3.0 Unported
This dataset contains gene and pathway mutation scores for 5,805 primary tumors from 23 different cancer types from The Cancer Genome Atlas (TCGA).
Gene mutation scores of 2,219 cancer-associated genes were calculated by normalizing the number of non-silent mutations in a gene (obtained from .maf files from TCGA) by the gene's length. We used SAMBAR (Subtyping Agglomerated Mutations By Annotation Relations) to calculate pathway mutation scores. In short, SAMBAR takes the sum of mutation scores of all genes belonging to a biological pathway and then corrects these scores for the pathway's gene set size and the number of times a gene is represented in the complete set of pathways. Please see our publication in the British Journal of Cancer for methodological details.
In the RData file "TCGA_SAMBAR.RData", we share the following objects:
- gene_scores: a 2219 by 5805 numeric matrix including gene (rows) mutation scores for each sample (columns).
- pathway_scores: a 1066 by 5805 numeric matrix including pathway (rows) mutation scores for each sample (columns).
The file "sample_tumor_annotation.RData" contains the object:
- sample_annotation: a 5805 by 2 character matrix including sample names (first column) and the tumor type the sample belongs to (TCGA Study Abbreviations).
This work was funded through a grant from the NVIDIA foundation (grant no. 2014-133322 (3953)). This work was additionally supported by a Postdoctoral Fellowship Program from the Charles A. King Trust Fund, Sara Elizabeth O'Brien Trust, Bank of America, N.A., co-Trustees.