ModSaRa: A computationally efficient R package for CNV identification

Feifei Xiao; Yue Niu; Ning Hao; Yanxun Xu; Zhilin Jin; Heping Zhang

doi:10.1093/bioinformatics/btx212

ModSaRa: A computationally efficient R package for CNV identification

Feifei Xiao, Yue Niu, Ning Hao, Yanxun Xu, Zhilin Jin, Heping Zhang

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

4 Scopus citations

Abstract

Summary: Chromosomal copy number variation (CNV) refers to a polymorphism that a DNA segment presents deletion or duplication in the population. The computational algorithms developed to identify this type of variation are usually of high computational complexity. Here we present a user-friendly R package, modSaRa, designed to perform copy number variants identification. The package is developed based on a change-point based method with optimal computational complexity and desirable accuracy. The current version of modSaRa package is a comprehensive tool with integration of preprocessing steps and main CNV calling steps.

Original language	English (US)
Pages (from-to)	2384-2385
Number of pages	2
Journal	Bioinformatics
Volume	33
Issue number	15
DOIs	https://doi.org/10.1093/bioinformatics/btx212
State	Published - Aug 1 2017

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btx212

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title = "ModSaRa: A computationally efficient R package for CNV identification",

abstract = "Summary: Chromosomal copy number variation (CNV) refers to a polymorphism that a DNA segment presents deletion or duplication in the population. The computational algorithms developed to identify this type of variation are usually of high computational complexity. Here we present a user-friendly R package, modSaRa, designed to perform copy number variants identification. The package is developed based on a change-point based method with optimal computational complexity and desirable accuracy. The current version of modSaRa package is a comprehensive tool with integration of preprocessing steps and main CNV calling steps.",

author = "Feifei Xiao and Yue Niu and Ning Hao and Yanxun Xu and Zhilin Jin and Heping Zhang",

note = "Funding Information: This research is supported in part by grant R01DA016750 from the National Institute on Drug Abuse, National Science Foundation Grant DMS-1309507 and the internal fund from the University of South Carolina. Publisher Copyright: {\textcopyright} The Author 2017. Published by Oxford University Press. All rights reserved.",

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doi = "10.1093/bioinformatics/btx212",

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T1 - ModSaRa

T2 - A computationally efficient R package for CNV identification

AU - Xiao, Feifei

AU - Niu, Yue

AU - Hao, Ning

AU - Xu, Yanxun

AU - Jin, Zhilin

AU - Zhang, Heping

N1 - Funding Information: This research is supported in part by grant R01DA016750 from the National Institute on Drug Abuse, National Science Foundation Grant DMS-1309507 and the internal fund from the University of South Carolina. Publisher Copyright: © The Author 2017. Published by Oxford University Press. All rights reserved.

PY - 2017/8/1

Y1 - 2017/8/1

N2 - Summary: Chromosomal copy number variation (CNV) refers to a polymorphism that a DNA segment presents deletion or duplication in the population. The computational algorithms developed to identify this type of variation are usually of high computational complexity. Here we present a user-friendly R package, modSaRa, designed to perform copy number variants identification. The package is developed based on a change-point based method with optimal computational complexity and desirable accuracy. The current version of modSaRa package is a comprehensive tool with integration of preprocessing steps and main CNV calling steps.

AB - Summary: Chromosomal copy number variation (CNV) refers to a polymorphism that a DNA segment presents deletion or duplication in the population. The computational algorithms developed to identify this type of variation are usually of high computational complexity. Here we present a user-friendly R package, modSaRa, designed to perform copy number variants identification. The package is developed based on a change-point based method with optimal computational complexity and desirable accuracy. The current version of modSaRa package is a comprehensive tool with integration of preprocessing steps and main CNV calling steps.

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ModSaRa: A computationally efficient R package for CNV identification

Abstract

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