| Literature DB >> 23975140 |
Avinash Ramu1, Michiel J Noordam, Rachel S Schwartz, Arthur Wuster, Matthew E Hurles, Reed A Cartwright, Donald F Conrad.
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.Entities:
Mesh:
Year: 2013 PMID: 23975140 PMCID: PMC4003501 DOI: 10.1038/nmeth.2611
Source DB: PubMed Journal: Nat Methods ISSN: 1548-7091 Impact factor: 28.547