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@ARTICLE{Shuai:177481,
      author       = {S. Shuai and PCAWGDrivers and
                      FunctionalInterpretationWorkingGroup and S. Gallinger and L.
                      Stein and PCAWGConsortium},
      title        = {{C}ombined burden and functional impact tests for cancer
                      driver discovery using {D}river{P}ower.},
      journal      = {Nature Communications},
      volume       = {11},
      number       = {1},
      issn         = {2041-1723},
      address      = {[London]},
      publisher    = {Nature Publishing Group UK},
      reportid     = {DKFZ-2021-02568},
      pages        = {734},
      year         = {2020},
      note         = {siehe Correction: DKFZ Autoren affiliiert im PCAWG
                      Consortium: https://inrepo02.dkfz.de/record/212435 /
                      https://doi.org/10.1038/s41467-022-32343-8},
      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.},
      keywords     = {Algorithms / Genome, Human / Genomics: methods / Humans /
                      MEF2 Transcription Factors: genetics / Mutation / Mutation
                      Rate / Neoplasms: genetics / Peptide Elongation Factor 1:
                      genetics / Receptors, G-Protein-Coupled: genetics / Software
                      / Whole Genome Sequencing / ADGRG6 protein, human (NLM
                      Chemicals) / EEF1A2 protein, human (NLM Chemicals) / MEF2
                      Transcription Factors (NLM Chemicals) / MEF2B protein, human
                      (NLM Chemicals) / Peptide Elongation Factor 1 (NLM
                      Chemicals) / Receptors, G-Protein-Coupled (NLM Chemicals)},
      cin          = {B080 / B330 / B370 / W610 / HD01 / B060 / B062 / B360 /
                      B066 / B240 / BE01 / B260 / B063 / W190 / B087},
      ddc          = {500},
      cid          = {I:(DE-He78)B080-20160331 / I:(DE-He78)B330-20160331 /
                      I:(DE-He78)B370-20160331 / I:(DE-He78)W610-20160331 /
                      I:(DE-He78)HD01-20160331 / I:(DE-He78)B060-20160331 /
                      I:(DE-He78)B062-20160331 / I:(DE-He78)B360-20160331 /
                      I:(DE-He78)B066-20160331 / I:(DE-He78)B240-20160331 /
                      I:(DE-He78)BE01-20160331 / I:(DE-He78)B260-20160331 /
                      I:(DE-He78)B063-20160331 / I:(DE-He78)W190-20160331 /
                      I:(DE-He78)B087-20160331},
      pnm          = {312 - Functional and structural genomics (POF3-312)},
      pid          = {G:(DE-HGF)POF3-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32024818},
      pmc          = {pmc:PMC7002750},
      doi          = {10.1038/s41467-019-13929-1},
      url          = {https://inrepo02.dkfz.de/record/177481},
}