DeNovoGear: De novo indel and point mutation discovery and phasing

Avinash Ramu; Michiel J. Noordam; Rachel S. Schwartz; Arthur Wuster; Matthew E. Hurles; Reed A. Cartwright; Donald F. Conrad

doi:10.1038/nmeth.2611

DeNovoGear: De novo indel and point mutation discovery and phasing

Avinash Ramu, Michiel J. Noordam, Rachel S. Schwartz, Arthur Wuster, Matthew E. Hurles, Reed A. Cartwright, Donald F. Conrad

Research output: Contribution to journal › Article › peer-review

126 Scopus citations

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)
Pages (from-to)	985-987
Number of pages	3
Journal	Nature Methods
Volume	10
Issue number	10
DOIs	https://doi.org/10.1038/nmeth.2611
State	Published - Oct 2013
Externally published	Yes

ASJC Scopus subject areas

Biotechnology
Biochemistry
Molecular Biology
Cell Biology

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10.1038/nmeth.2611

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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.",

author = "Avinash Ramu and Noordam, {Michiel J.} and Schwartz, {Rachel S.} and Arthur Wuster and Hurles, {Matthew E.} and Cartwright, {Reed A.} and Conrad, {Donald F.}",

note = "Funding Information: We thank R. Hardwick for assistance with primer design, V. Plagnol and H. Li for helpful discussion, and members of the 1000 Genomes community for generating software, data and resources that we used as part of this project. This research was supported in part by Wellcome Trust grant WT098051.",

year = "2013",

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doi = "10.1038/nmeth.2611",

language = "English (US)",

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pages = "985--987",

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T2 - De novo indel and point mutation discovery and phasing

AU - Ramu, Avinash

AU - Noordam, Michiel J.

AU - Schwartz, Rachel S.

AU - Wuster, Arthur

AU - Hurles, Matthew E.

AU - Cartwright, Reed A.

AU - Conrad, Donald F.

N1 - Funding Information: We thank R. Hardwick for assistance with primer design, V. Plagnol and H. Li for helpful discussion, and members of the 1000 Genomes community for generating software, data and resources that we used as part of this project. This research was supported in part by Wellcome Trust grant WT098051.

PY - 2013/10

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AB - 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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DeNovoGear: De novo indel and point mutation discovery and phasing

Abstract

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