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

Bioinformatics. 2017 Aug 1;33(15):2384-2385. doi: 10.1093/bioinformatics/btx212.

Authors

Feifei Xiao¹, Yue Niu², Ning Hao², Yanxun Xu³, Zhilin Jin³, Heping Zhang⁴

Affiliations

¹ Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC 29201, USA.
² Department of Mathematics, University of Arizona, Tucson, AZ 85721, USA.
³ Department of Applied Mathematics & Statistics, Johns Hopkins University, Baltimore, MD 21218, USA.
⁴ Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.

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.

Availability and implementation: modSaRa is an R package written in R, C ++ and Rcpp and is now freely available for download at http://c2s2.yale.edu/software/modSaRa .

Contact: heping.zhang@yale.edu.

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

Algorithms
DNA Copy Number Variations*
Genomics / methods
Humans
Sequence Analysis, DNA / methods*
Software*

Abstract

MeSH terms

Grants and funding