1. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data
- Author
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Xi Wang, Xiao-Wo Wang, Likun Wang, Zhixing Feng, and Xuegong Zhang
- Subjects
Statistics and Probability ,Genetics ,Base Sequence ,Sequence analysis ,Sequence Analysis, RNA ,Gene Expression Profiling ,Molecular Sequence Data ,RNA ,RNA-Seq ,Biology ,Biochemistry ,DNA sequencing ,Computer Science Applications ,Computational Mathematics ,R package ,Differentially expressed genes ,Computational Theory and Mathematics ,Gene expression ,Programming Languages ,Molecular Biology ,Gene ,Algorithms ,Software ,Oligonucleotide Array Sequence Analysis - Abstract
Summary: High-throughput RNA sequencing (RNA-seq) is rapidly emerging as a major quantitative transcriptome profiling platform. Here, we present DEGseq, an R package to identify differentially expressed genes or isoforms for RNA-seq data from different samples. In this package, we integrated three existing methods, and introduced two novel methods based on MA-plot to detect and visualize gene expression difference. Availability: The R package and a quick-start vignette is available at http://bioinfo.au.tsinghua.edu.cn/software/degseq Contact: xwwang@tsinghua.edu.cn; zhangxg@tsinghua.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.
- Published
- 2009