TitanCNA

TitanCNA introduces a probabilistic model to enhance our understanding of the evolutionary dynamics within cancer genomes by focusing on copy number alterations (CNA) and loss of heterozygosity (LOH). This model stands out by adeptly inferring CNA and LOH events while accounting for the presence of mixed cell populations within a single tumor, estimating the proportion of cells carrying each event. This approach marks a significant departure from the traditional focus on somatic point mutations, addressing the need for computational methods to unravel the complexities of CNA and LOH in whole-genome sequencing data.

Topic

Whole genome sequencing;DNA structural variation;Oncology;Statistics and probability;Data mining

Detail

  • Operation: Polymorphism detection;Sequence analysis;Structural variation detection

  • Software interface: Command-line user interface,Library

  • Language: R

  • License: The GNU General Public License v3.0

  • Cost: Free

  • Version name: 1.40.0

  • Credit: The Canadian Institutes for Health Research (CIHR), Canadian Cancer Society Research Institute, and the Terry Fox Research Institute, The Michael Smith Foundation for Health Research and the Natural Sciences and Engineering Research Council of Canada.

  • Input: -

  • Output: -

  • Contact: Gavin Ha gha@fredhutch.org

  • Collection: -

  • Maturity: Stable

Publications

  • TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data.
  • Ha G, et al. TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data. TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data. 2014; 24:1881-93. doi: 10.1101/gr.180281.114
  • https://doi.org/10.1101/gr.180281.114
  • PMID: 25060187
  • PMC: PMC4216928

Download and documentation

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