DeNovoGear: de novo indel and point mutation discovery and phasing
A Ramu, MJ Noordam, RS Schwartz, A Wuster… - Nature …, 2013 - nature.com
Nature methods, 2013•nature.com
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.
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.
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.
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