Title Tcc: Differential Expression Analysis for Tag Count Data with Robust Normalization Strategies
نویسندگان
چکیده
December 22, 2016 Type Package Title TCC: Differential expression analysis for tag count data with robust normalization strategies Version 1.14.0 Author Jianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji Kadota Maintainer Jianqiang Sun , Tomoaki Nishiyama Description This package provides a series of functions for performing differential expression analysis from RNA-seq count data using robust normalization strategy (called DEGES). The basic idea of DEGES is that potential differentially expressed genes or transcripts (DEGs) among compared samples should be removed before data normalization to obtain a well-ranked gene list where true DEGs are top-ranked and non-DEGs are bottom ranked. This can be done by performing a multi-step normalization strategy (called DEGES for DEG elimination strategy). A major characteristic of TCC is to provide the robust normalization methods for several kinds of count data (two-group with or without replicates, multi-group/multi-factor, and so on) by virtue of the use of combinations of functions in depended packages. Depends R (>= 2.15), methods, DESeq, DESeq2, edgeR, baySeq, ROC Imports samr Suggests RUnit, BiocGenerics Enhances snow License GPL-2 Copyright Authors listed above biocViews Sequencing, DifferentialExpression, RNASeq NeedsCompilation no
منابع مشابه
Package 'tcc' Title Tcc: Differential Expression Analysis for Tag Count Data with Robust Normalization Strategies
April 26, 2017 Type Package Title TCC: Differential expression analysis for tag count data with robust normalization strategies Version 1.16.0 Author Jianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji Kadota Maintainer Jianqiang Sun , Tomoaki Nishiyama Description This package provides a series of functions for performing dif...
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The R/Bioconductor package, TCC, provides users with a robust and accurate framework to perform differential expression (DE) analysis of tag count data. We recently developed a multi-step normalization method (TbT; Kadota et al., 2012 [3]) for two-group RNA-seq data. The strategy (called DEGES) is to remove data that are potential differentially expressed genes (DEGs) before performing the data...
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