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000177481 037__ $$aDKFZ-2021-02568
000177481 041__ $$aEnglish
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000177481 1001_ $$aShuai, Shimin$$b0
000177481 245__ $$aCombined burden and functional impact tests for cancer driver discovery using DriverPower.
000177481 260__ $$a[London]$$bNature Publishing Group UK$$c2020
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000177481 500__ $$asiehe Correction: DKFZ Autoren affiliiert im PCAWG Consortium: https://inrepo02.dkfz.de/record/212435   /  https://doi.org/10.1038/s41467-022-32343-8
000177481 520__ $$aThe 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.
000177481 536__ $$0G:(DE-HGF)POF3-312$$a312 - Functional and structural genomics (POF3-312)$$cPOF3-312$$fPOF III$$x0
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000177481 650_7 $$2NLM Chemicals$$aADGRG6 protein, human
000177481 650_7 $$2NLM Chemicals$$aEEF1A2 protein, human
000177481 650_7 $$2NLM Chemicals$$aMEF2 Transcription Factors
000177481 650_7 $$2NLM Chemicals$$aMEF2B protein, human
000177481 650_7 $$2NLM Chemicals$$aPeptide Elongation Factor 1
000177481 650_7 $$2NLM Chemicals$$aReceptors, G-Protein-Coupled
000177481 650_2 $$2MeSH$$aAlgorithms
000177481 650_2 $$2MeSH$$aGenome, Human
000177481 650_2 $$2MeSH$$aGenomics: methods
000177481 650_2 $$2MeSH$$aHumans
000177481 650_2 $$2MeSH$$aMEF2 Transcription Factors: genetics
000177481 650_2 $$2MeSH$$aMutation
000177481 650_2 $$2MeSH$$aMutation Rate
000177481 650_2 $$2MeSH$$aNeoplasms: genetics
000177481 650_2 $$2MeSH$$aPeptide Elongation Factor 1: genetics
000177481 650_2 $$2MeSH$$aReceptors, G-Protein-Coupled: genetics
000177481 650_2 $$2MeSH$$aSoftware
000177481 650_2 $$2MeSH$$aWhole Genome Sequencing
000177481 7001_ $$aPCAWGDrivers$$b1
000177481 7001_ $$aFunctionalInterpretationWorkingGroup$$b2
000177481 7001_ $$aGallinger, Steven$$b3
000177481 7001_ $$aStein, Lincoln$$b4
000177481 7001_ $$aPCAWGConsortium$$b5
000177481 773__ $$0PERI:(DE-600)2553671-0$$a10.1038/s41467-019-13929-1$$gVol. 11, no. 1, p. 734$$n1$$p734$$tNature Communications$$v11$$x2041-1723$$y2020
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000177481 9141_ $$y2020
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