Jan 26, 2014

A Powerful Approach for Identification of Differentially Transcribed mRNA Isoforms

BioRxiv : the Preprint Server for Biology
Yuande Tan, Joel R Neilson


Next generation sequencing is being increasingly used for transcriptome-wide analysis of differential gene expression. The primary goal in profiling expression is to identify genes or RNA isoforms differentially expressed between specific conditions. Yet, the next generation sequence-based count data are essentially different from the microarray data that are continuous type, therefore, the statistical methods developed well over the last decades cannot be applicable. For this reason, a variety of new statistical methods based on count data of transcript reads has been correspondingly developed. But currently the transcriptomic count data coming only from a few replicate libraries have high technical noise and small sample size bias, performances of these new methods are not desirable. We here developed a new statistical method specifically applicable to small sample count data called mBeta t-test for identifying differentially expressed gene or isoforms on the basis of the Beta t-test. The results obtained from simulated and real data showed that the mBeta t-test method significantly outperformed the existing statistical methods in all given scenarios. Findings of our method were validated by qRT-PCR experiments. The mBeta t-t...Continue Reading

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Mentioned in this Paper

RNA Isoforms
Tissue-Specific Gene Expression
Gene Expression
Cell Differentiation Process
Quantitative Reverse Transcriptase PCR
Massively-Parallel Sequencing
Protein Isoforms
Base Sequence

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