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 language | English (US) |
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Pages (from-to) | 985-987 |
Number of pages | 3 |
Journal | Nature Methods |
Volume | 10 |
Issue number | 10 |
DOIs | |
State | Published - Oct 2013 |
ASJC Scopus subject areas
- Biotechnology
- Biochemistry
- Molecular Biology
- Cell Biology