Journal Article

DKFZ-2021-02568

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Combined burden and functional impact tests for cancer driver discovery using DriverPower.

Shuai, S. ; PCAWGDrivers ; FunctionalInterpretationWorkingGroup ; Gallinger, S. ; Stein, L. ; PCAWGConsortium

2020
Nature Publishing Group UK [London]

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Please use a persistent id in citations: doi:10.1038/s41467-019-13929-1

Abstract: 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% of the regional variance in the mutation rate across multiple tumour types. By incorporating functional impact scores, we are able to further increase the accuracy of driver discovery. Testing across a collection of 2583 cancer genomes from the PCAWG project, DriverPower identifies 217 coding and 95 non-coding driver candidates. Comparing to six published methods used by the PCAWG Drivers and Functional Interpretation Working Group, DriverPower has the highest F1 score for both coding and non-coding driver discovery. This demonstrates that DriverPower is an effective framework for computational driver discovery.

Keyword(s): Algorithms (MeSH) ; Genome, Human (MeSH) ; Genomics: methods (MeSH) ; Humans (MeSH) ; MEF2 Transcription Factors: genetics (MeSH) ; Mutation (MeSH) ; Mutation Rate (MeSH) ; Neoplasms: genetics (MeSH) ; Peptide Elongation Factor 1: genetics (MeSH) ; Receptors, G-Protein-Coupled: genetics (MeSH) ; Software (MeSH) ; Whole Genome Sequencing (MeSH) ; ADGRG6 protein, human ; EEF1A2 protein, human ; MEF2 Transcription Factors ; MEF2B protein, human ; Peptide Elongation Factor 1 ; Receptors, G-Protein-Coupled

Note: siehe Correction: DKFZ Autoren affiliiert im PCAWG Consortium: https://inrepo02.dkfz.de/record/212435 / https://doi.org/10.1038/s41467-022-32343-8

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Contributing Institute(s):

1. Theoretische Bioinformatik (B080)
2. Angewandte Bioinformatik (B330)
3. Epigenomik (B370)
4. Core Facility Omics IT (W610)
5. DKTK HD zentral (HD01)
6. B060 Molekulare Genetik (B060)
7. B062 Pädiatrische Neuroonkologie (B062)
8. Pädiatrische Gliomforschung (B360)
9. B066 Chromatin-Netzwerke (B066)
10. Bioinformatik und Omics Data Analytics (B240)
11. DKTK Koordinierungsstelle Berlin (BE01)
12. B260 Bioinformatik der Genomik und Systemgenetik (B260)
13. B063 Krebsgenomforschung (B063)
14. Hochdurchsatz-Sequenzierung (W190)
15. B087 Neuroblastom Genomik (B087)

Research Program(s):

1. 312 - Functional and structural genomics (POF3-312) (POF3-312)

Appears in the scientific report 2020

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