cn.mops

DOI:10.18129 / B9.bioc.cn.mops

这个包是3.15版本Bioconductor;的稳定,最新的发布版本,请参阅cn.mops。

cn.mops- Mixture of Poissons for CNV detection in NGS data

Bioconductor版本:3.15

cn.mops(Copy Number estimation by a Mixture Of PoissonS) is a data processing pipeline for copy number variations and aberrations (CNVs and CNAs) from next generation sequencing (NGS) data. The package supplies functions to convert BAM files into read count matrices or genomic ranges objects, which are the input objects for cn.mops. cn.mops models the depths of coverage across samples at each genomic position. Therefore, it does not suffer from read count biases along chromosomes. Using a Bayesian approach, cn.mops decomposes read variations across samples into integer copy numbers and noise by its mixture components and Poisson distributions, respectively. cn.mops guarantees a low FDR because wrong detections are indicated by high noise and filtered out. cn.mops is very fast and written in C++.

作者:京特·Klambauer (aut) Gundula Povysil (cre)

维护人员:Gundula Povysil < Povysil在bioinf.jku.at >

安装

安装这个包,开始R(版本“4.2”)并输入:

如果(!要求(“BiocManager”,悄悄地= TRUE)) install.packages (“BiocManager”) BiocManager::安装(“cn.mops”)

R的旧版本,请参考适当的Bioconductor释放。

文档

查看文档的版本这个包安装在您的系统,开始R和输入:

browseVignettes (“cn.mops”)

PDF	R脚本	cn.mops: Manual for the R package
PDF		参考手册

细节

biocViews	CellBiology,CopyNumberVariation,遗传学,人类基因组单体型图,Homo_sapiens,测序,软件
版本	1.42.0
Bioconductor自	BioC 2.9 (r - 2.14)(11年)
许可证	LGPL (> = 2.0)
取决于	R(> = 3.5.0)、方法、效用,数据,图形,平行,GenomicRanges
进口	BiocGenerics,Biobase,IRanges,Rsamtools,GenomeInfoDb,S4Vectors,exomeCopy
链接
建议	DNAcopy
SystemRequirements
增强了
URL	http://www.bioinf.jku.at/software/cnmops/cnmops.html
取决于我	panelcn.mops
进口我	CopyNumberPlots
建议我	CNVgears
我的链接
构建报告

包档案

遵循bob 体育网址 指示在R会话中使用这个包。

源包	cn.mops_1.42.0.tar.gz
Windows二进制	cn.mops_1.42.0.zip(64位)
macOS二进制(x86_64)	cn.mops_1.42.0.tgz
源库	git克隆https://git.bioconductor.org/packages/cn.mops
源库(开发人员访问)	git克隆git@git.bioconductor.org:包/ cn.mops
包短Url	//www.anjoumacpherson.com/packages/cn.mops/
包下载报告	下载数据