Abstract
Summary: 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. Availability and implementation: The R package with its source code and documentation are freely available at http://www-personal.umich.edu/∼jianghui/rseqnp/.
Original language | English (US) |
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Pages (from-to) | 2222-2224 |
Number of pages | 3 |
Journal | Bioinformatics |
Volume | 31 |
Issue number | 13 |
DOIs | |
State | Published - Jul 1 2015 |
Externally published | Yes |
ASJC Scopus subject areas
- Statistics and Probability
- Biochemistry
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics