DeNovoGear: De novo indel and point mutation discovery and phasing

Avinash Ramu, Michiel J. Noordam, Rachel S. Schwartz, Arthur Wuster, Matthew E. Hurles, Reed A. Cartwright, Donald F. Conrad

Research output: Contribution to journalArticlepeer-review

83 Scopus citations

Abstract

We present DeNovoGear software for analyzing de novo mutations from familial and somatic tissue sequencing data. DeNovoGear uses likelihood-based error modeling to reduce the false positive rate of mutation discovery in exome analysis and fragment information to identify the parental origin of germ-line mutations. We used DeNovoGear on human whole-genome sequencing data to produce a set of predicted de novo insertion and/or deletion (indel) mutations with a 95% validation rate.

Original languageEnglish (US)
Pages (from-to)985-987
Number of pages3
JournalNature Methods
Volume10
Issue number10
DOIs
StatePublished - Oct 2013

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology

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