Somaticsniper: Identification of somatic point mutations in whole genome sequencing data

David E. Larson; Christopher C. Harris; Ken Chen; Daniel C. Koboldt; Travis E. Abbott; David J. Dooling; Timothy J. Ley; Elaine R. Mardis; Richard K. Wilson; Li Ding

doi:10.1093/bioinformatics/btr665

Somaticsniper: Identification of somatic point mutations in whole genome sequencing data

David E. Larson, Christopher C. Harris, Ken Chen, Daniel C. Koboldt, Travis E. Abbott, David J. Dooling, Timothy J. Ley, Elaine R. Mardis, Richard K. Wilson, Li Ding

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

468 Scopus citations

Abstract

Motivation: The sequencing of tumors and their matched normals is frequently used to study the genetic composition of cancer. Despite this fact, there remains a dearth of available software tools designed to compare sequences in pairs of samples and identify sites that are likely to be unique to one sample.Results: In this article, we describe the mathematical basis of our SomaticSniper software for comparing tumor and normal pairs. We estimate its sensitivity and precision, and present several common sources of error resulting in miscalls.

Original language	English
Article number	btr665
Pages (from-to)	311-317
Number of pages	7
Journal	Bioinformatics
Volume	28
Issue number	3
DOIs	https://doi.org/10.1093/bioinformatics/btr665
State	Published - Feb 2012

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10.1093/bioinformatics/btr665

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title = "Somaticsniper: Identification of somatic point mutations in whole genome sequencing data",

abstract = "Motivation: The sequencing of tumors and their matched normals is frequently used to study the genetic composition of cancer. Despite this fact, there remains a dearth of available software tools designed to compare sequences in pairs of samples and identify sites that are likely to be unique to one sample.Results: In this article, we describe the mathematical basis of our SomaticSniper software for comparing tumor and normal pairs. We estimate its sensitivity and precision, and present several common sources of error resulting in miscalls.",

author = "Larson, {David E.} and Harris, {Christopher C.} and Ken Chen and Koboldt, {Daniel C.} and Abbott, {Travis E.} and Dooling, {David J.} and Ley, {Timothy J.} and Mardis, {Elaine R.} and Wilson, {Richard K.} and Li Ding",

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AU - Harris, Christopher C.

AU - Chen, Ken

AU - Koboldt, Daniel C.

AU - Abbott, Travis E.

AU - Dooling, David J.

AU - Ley, Timothy J.

AU - Mardis, Elaine R.

AU - Wilson, Richard K.

AU - Ding, Li

PY - 2012/2

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N2 - Motivation: The sequencing of tumors and their matched normals is frequently used to study the genetic composition of cancer. Despite this fact, there remains a dearth of available software tools designed to compare sequences in pairs of samples and identify sites that are likely to be unique to one sample.Results: In this article, we describe the mathematical basis of our SomaticSniper software for comparing tumor and normal pairs. We estimate its sensitivity and precision, and present several common sources of error resulting in miscalls.

AB - Motivation: The sequencing of tumors and their matched normals is frequently used to study the genetic composition of cancer. Despite this fact, there remains a dearth of available software tools designed to compare sequences in pairs of samples and identify sites that are likely to be unique to one sample.Results: In this article, we describe the mathematical basis of our SomaticSniper software for comparing tumor and normal pairs. We estimate its sensitivity and precision, and present several common sources of error resulting in miscalls.

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Somaticsniper: Identification of somatic point mutations in whole genome sequencing data

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