DeNovoGear: De Novo Indel and Point Mutation Discovery and Phasing

Overview

Journal Nat Methods

Specialties Biomedical Engineering
Pathology

Date 2013 Aug 27

PMID 23975140

Citations 101

Authors

Avinash Ramu

Michiel J Noordam

Rachel S Schwartz

Arthur Wuster

Matthew E Hurles

Reed A Cartwright

Donald F Conrad

Affiliations

Soon will be listed here.

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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