modSaRa: a computationally efficient R package for CNV identification | Zendy

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

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modSaRa: a computationally efficient R package for CNV identification

Author(s) -

Feifei Xiao,

Yue Niu,

Ning Hao,

Yanxun Xu,

Zhilin Jin,

Heping Zhang

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx212

Subject(s) - preprocessor , computer science , copy number variation , r package , identification (biology) , software package , software , computational complexity theory , population , algorithm , artificial intelligence , programming language , biology , genetics , genome , botany , demography , sociology , gene

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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