<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Xiao F</submitter><funding>NCATS NIH HHS</funding><funding>NIDA NIH HHS</funding><pagination>2384-2385</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC5860124</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>33(15)</volume><pubmed_abstract>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.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 .heping.zhang@yale.edu.Supplementary data are available at Bioinformatics online.</pubmed_abstract><journal>Bioinformatics (Oxford, England)</journal><pubmed_title>modSaRa: a computationally efficient R package for CNV identification.</pubmed_title><pmcid>PMC5860124</pmcid><funding_grant_id>R01 DA016750</funding_grant_id><funding_grant_id>UL1 TR001863</funding_grant_id><pubmed_authors>Hao N</pubmed_authors><pubmed_authors>Zhang H</pubmed_authors><pubmed_authors>Xiao F</pubmed_authors><pubmed_authors>Jin Z</pubmed_authors><pubmed_authors>Niu Y</pubmed_authors><pubmed_authors>Xu Y</pubmed_authors></additional><is_claimable>false</is_claimable><name>modSaRa: a computationally efficient R package for CNV identification.</name><description>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.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 .heping.zhang@yale.edu.Supplementary data are available at Bioinformatics online.</description><dates><release>2017-01-01T00:00:00Z</release><publication>2017 Aug</publication><modification>2021-02-20T12:14:36Z</modification><creation>2019-03-26T23:48:52Z</creation></dates><accession>S-EPMC5860124</accession><cross_references><pubmed>28453611</pubmed><doi>10.1093/bioinformatics/btx212</doi></cross_references></HashMap>