TY  - JOUR
AU  - Shuai, Shimin
AU  - PCAWGDrivers
AU  - FunctionalInterpretationWorkingGroup
AU  - Gallinger, Steven
AU  - Stein, Lincoln
AU  - PCAWGConsortium
TI  - Combined burden and functional impact tests for cancer driver discovery using DriverPower.
JO  - Nature Communications
VL  - 11
IS  - 1
SN  - 2041-1723
CY  - [London]
PB  - Nature Publishing Group UK
M1  - DKFZ-2021-02568
SP  - 734
PY  - 2020
N1  - siehe Correction: DKFZ Autoren affiliiert im PCAWG Consortium: https://inrepo02.dkfz.de/record/212435   /  https://doi.org/10.1038/s41467-022-32343-8
AB  - The discovery of driver mutations is one of the key motivations for cancer genome sequencing. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we describe DriverPower, a software package that uses mutational burden and functional impact evidence to identify driver mutations in coding and non-coding sites within cancer whole genomes. Using a total of 1373 genomic features derived from public sources, DriverPower's background mutation model explains up to 93
KW  - Algorithms
KW  - Genome, Human
KW  - Genomics: methods
KW  - Humans
KW  - MEF2 Transcription Factors: genetics
KW  - Mutation
KW  - Mutation Rate
KW  - Neoplasms: genetics
KW  - Peptide Elongation Factor 1: genetics
KW  - Receptors, G-Protein-Coupled: genetics
KW  - Software
KW  - Whole Genome Sequencing
KW  - ADGRG6 protein, human (NLM Chemicals)
KW  - EEF1A2 protein, human (NLM Chemicals)
KW  - MEF2 Transcription Factors (NLM Chemicals)
KW  - MEF2B protein, human (NLM Chemicals)
KW  - Peptide Elongation Factor 1 (NLM Chemicals)
KW  - Receptors, G-Protein-Coupled (NLM Chemicals)
LB  - PUB:(DE-HGF)16
C6  - pmid:32024818
C2  - pmc:PMC7002750
DO  - DOI:10.1038/s41467-019-13929-1
UR  - https://inrepo02.dkfz.de/record/177481
ER  -