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@ARTICLE{Rubanova:177483,
      author       = {Y. Rubanova and R. Shi and C. F. Harrigan and R. Li and J.
                      Wintersinger and N. Sahin and A. Deshwar and PCAWGEvolution
                      and H. W. Group and Q. Morris and PCAWGConsortium},
      title        = {{R}econstructing evolutionary trajectories of mutation
                      signature activities in cancer using {T}rack{S}ig.},
      journal      = {Nature Communications},
      volume       = {11},
      number       = {1},
      issn         = {2041-1723},
      address      = {[London]},
      publisher    = {Nature Publishing Group UK},
      reportid     = {DKFZ-2021-02570},
      pages        = {731},
      year         = {2020},
      note         = {siehe Correction: DKFZ Autoren affiliiert im PCAWG
                      Consortium: https://inrepo02.dkfz.de/record/212434 /
                      https://doi.org/10.1038/s41467-022-32336-7},
      abstract     = {The type and genomic context of cancer mutations depend on
                      their causes. These causes have been characterized using
                      signatures that represent mutation types that co-occur in
                      the same tumours. However, it remains unclear how mutation
                      processes change during cancer evolution due to the lack of
                      reliable methods to reconstruct evolutionary trajectories of
                      mutational signature activity. 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 present
                      TrackSig, a new method that reconstructs these trajectories
                      using optimal, joint segmentation and deconvolution of
                      mutation type and allele frequencies from a single tumour
                      sample. In simulations, we find TrackSig has a $3-5\%$
                      activity reconstruction error, and $12\%$ false detection
                      rate. It outperforms an aggressive baseline in situations
                      with branching evolution, CNA gain, and neutral mutations.
                      Applied to data from 2658 tumours and 38 cancer types,
                      TrackSig permits pan-cancer insight into evolutionary
                      changes in mutational processes.},
      keywords     = {Computational Biology: methods / Computer Simulation /
                      Evolution, Molecular / Gene Frequency / Genome, Human /
                      Humans / Mutation / Neoplasms: genetics / Neoplasms:
                      pathology / Polymorphism, Single Nucleotide / Whole Genome
                      Sequencing},
      cin          = {B370 / B330 / B240 / HD01 / B080 / B060 / B062 / B360 /
                      B260 / BE01 / B063 / B087 / W610 / W190 / B066},
      ddc          = {500},
      cid          = {I:(DE-He78)B370-20160331 / I:(DE-He78)B330-20160331 /
                      I:(DE-He78)B240-20160331 / I:(DE-He78)HD01-20160331 /
                      I:(DE-He78)B080-20160331 / I:(DE-He78)B060-20160331 /
                      I:(DE-He78)B062-20160331 / I:(DE-He78)B360-20160331 /
                      I:(DE-He78)B260-20160331 / I:(DE-He78)BE01-20160331 /
                      I:(DE-He78)B063-20160331 / I:(DE-He78)B087-20160331 /
                      I:(DE-He78)W610-20160331 / I:(DE-He78)W190-20160331 /
                      I:(DE-He78)B066-20160331},
      pnm          = {312 - Functional and structural genomics (POF3-312)},
      pid          = {G:(DE-HGF)POF3-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32024834},
      pmc          = {pmc:PMC7002414},
      doi          = {10.1038/s41467-020-14352-7},
      url          = {https://inrepo02.dkfz.de/record/177483},
}