rSeqNP: a non-parametric approach for detecting differential expression and splicing from RNA-Seq data.
basic_science · Level V
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- Record sourced from PubMed, PMID 25717189.
- Also identified by DOI 10.1093/bioinformatics/btv119 and PMC identifier 4481847.
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Abstract
High-throughput sequencing of transcriptomes (RNA-Seq) has become a powerful tool to study gene expression. Here we present an R package, rSeqNP, which implements a non-parametric approach to test for differential expression and splicing from RNA-Seq data. rSeqNP uses permutation tests to access statistical significance and can be applied to a variety of experimental designs. By combining information across isoforms, rSeqNP is able to detect more differentially expressed or spliced genes from RNA-Seq data. The R package with its source code and documentation are freely available at http://www-personal.umich.edu/∼jianghui/rseqnp/. jianghui@umich.edu Supplementary data are available at Bioinformatics online.
Medical subject headings
- Computational Biology
- High-Throughput Nucleotide Sequencing
- RNA
- RNA Splicing
- Sequence Analysis, RNA
- Software
- Statistics, Nonparametric