rSeqNP: A non-parametric approach for detecting differential expression and splicing from RNA-Seq data

High-throughput sequencing of transcriptomes (RNA-Seq) has become a powerful tool to study gene expression. Here researchers from the University of Michigan 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.

Availability: The R package with its source code and documentation are freely available at http://www-personal.umich.edu/~jianghui/rseqnp/

Contact: jianghui@umich.edu

Shi Y, Chinnaiyan AM, Jiang H. (2015) rSeqNP: A non-parametric approach for detecting differential expression and splicing from RNA-Seq data. Bioinformatics [Epub ahead of print]. [abstract]

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