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A statistical method for detecting differentially expressed SNVs based on next-generation RNA-seq data.
- Source :
-
Biometrics . Mar2017, Vol. 73 Issue 1, p42-51. 10p. - Publication Year :
- 2017
-
Abstract
- In this article, we propose a new statistical method-MutRSeq-for detecting differentially expressed single nucleotide variants (SNVs) based on RNA-seq data. Specifically, we focus on nonsynonymous mutations and employ a hierarchical likelihood approach to jointly model observed mutation events as well as read count measurements from RNA-seq experiments. We then introduce a likelihood ratio-based test statistic, which detects changes not only in overall expression levels, but also in allele-specific expression patterns. In addition, this method can jointly test multiple mutations in one gene/pathway. The simulation studies suggest that the proposed method achieves better power than a few competitors under a range of different settings. In the end, we apply this method to a breast cancer data set and identify genes with nonsynonymous mutations differentially expressed between the triple negative breast cancer tumors and other subtypes of breast cancer tumors. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0006341X
- Volume :
- 73
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Biometrics
- Publication Type :
- Academic Journal
- Accession number :
- 122015589
- Full Text :
- https://doi.org/10.1111/biom.12548