title: DeNovoGear: de novo indel and point mutation discovery and phasing.
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.
authors: 1] Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA. [2].
authors: Avinash
authors: A
authors: Ramu
authors: Michiel J
authors: MJ
authors: Noordam
authors: Rachel S
authors: RS
authors: Schwartz
authors: Arthur
authors: A
authors: Wuster
authors: Matthew E
authors: ME
authors: Hurles
authors: Reed A
authors: RA
authors: Cartwright
authors: Donald F
authors: DF
authors: Conrad
mesh_terms: D059472:Exome; D017353:Gene Deletion; D015894:Genome, Human / Q000235:genetics*; D016045:Human Genome Project; D006801:Humans; D054643:INDEL Mutation; D016013:Likelihood Functions; D008957:Models, Genetic; D016254:Mutagenesis, Insertional; D017354:Point Mutation; D012984:Software
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