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@ARTICLE{Feuerbach:143879,
      author       = {L. Feuerbach$^*$ and L. Sieverling$^*$ and K. I. Deeg$^*$
                      and P. Ginsbach$^*$ and B. Hutter$^*$ and I. Buchhalter$^*$
                      and P. A. Northcott$^*$ and S. S. Mughal$^*$ and P.
                      Chudasama$^*$ and H. Glimm$^*$ and C. Scholl$^*$ and P.
                      Lichter$^*$ and S. Fröhling$^*$ and S. M. Pfister$^*$ and
                      D. T. W. Jones$^*$ and K. Rippe$^*$ and B. Brors$^*$},
      title        = {{T}elomere{H}unter - in silico estimation of telomere
                      content and composition from cancer genomes.},
      journal      = {BMC bioinformatics},
      volume       = {20},
      number       = {1},
      issn         = {1471-2105},
      address      = {Heidelberg},
      publisher    = {Springer},
      reportid     = {DKFZ-2019-01441},
      pages        = {272},
      year         = {2019},
      abstract     = {Establishment of telomere maintenance mechanisms is a
                      universal step in tumor development to achieve replicative
                      immortality. These processes leave molecular footprints in
                      cancer genomes in the form of altered telomere content and
                      aberrations in telomere composition. To retrieve these
                      telomere characteristics from high-throughput sequencing
                      data the available computational approaches need to be
                      extended and optimized to fully exploit the information
                      provided by large scale cancer genome data sets.We here
                      present TelomereHunter, a software for the detailed
                      characterization of telomere maintenance mechanism
                      footprints in the genome. The tool is implemented for the
                      analysis of large cancer genome cohorts and provides a
                      variety of diagnostic diagrams as well as machine-readable
                      output for subsequent analysis. A novel key feature is the
                      extraction of singleton telomere variant repeats, which
                      improves the identification and subclassification of the
                      alternative lengthening of telomeres phenotype. We find that
                      whole genome sequencing-derived telomere content estimates
                      strongly correlate with telomere qPCR measurements
                      (r = 0.94). For the first time, we determine the
                      correlation of in silico telomere content quantification
                      from whole genome sequencing and whole genome bisulfite
                      sequencing data derived from the same tumor sample
                      (r = 0.78). An analogous comparison of whole exome
                      sequencing data and whole genome sequencing data measured
                      slightly lower correlation (r = 0.79). However, this is
                      considerably improved by normalization with matched controls
                      (r = 0.91).TelomereHunter provides new functionality for
                      the analysis of the footprints of telomere maintenance
                      mechanisms in cancer genomes. Besides whole genome
                      sequencing, whole exome sequencing and whole genome
                      bisulfite sequencing are suited for in silico telomere
                      content quantification, especially if matched control
                      samples are available. The software runs under a GPL license
                      and is available at
                      https://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html
                      .},
      cin          = {B330 / B066 / B080 / B340 / B290 / B060 / B360 / L101 /
                      B062 / L301 / B280},
      ddc          = {610},
      cid          = {I:(DE-He78)B330-20160331 / I:(DE-He78)B066-20160331 /
                      I:(DE-He78)B080-20160331 / I:(DE-He78)B340-20160331 /
                      I:(DE-He78)B290-20160331 / I:(DE-He78)B060-20160331 /
                      I:(DE-He78)B360-20160331 / I:(DE-He78)L101-20160331 /
                      I:(DE-He78)B062-20160331 / I:(DE-He78)L301-20160331 /
                      I:(DE-He78)B280-20160331},
      pnm          = {312 - Functional and structural genomics (POF3-312)},
      pid          = {G:(DE-HGF)POF3-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31138115},
      doi          = {10.1186/s12859-019-2851-0},
      url          = {https://inrepo02.dkfz.de/record/143879},
}