ArticleBioinformatics (Oxford, England)2017
modSaRa: a computationally efficient R package for CNV identification.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Replication stress increases de novo CNVs across the malaria parasite genome.Nucleic acids research · 2026Article
- Replication stress increases de novo CNVs across the malaria parasite genome.bioRxiv : the preprint server for biology · 2025Article
- HapCNV: A Comprehensive Framework for CNV Detection in Low-input DNA Sequencing Data.bioRxiv : the preprint server for biology · 2025Article
- Shall genomic correlation structure be considered in copy number variants detection?Briefings in bioinformatics · 2021Article
- An accurate and powerful method for copy number variation detection.Bioinformatics (Oxford, England) · 2019Article
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Authors and funding
6 authors.
Funding
Abstract
summaryChromosomal 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.
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