EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data.

ABSTRACT:

Background

RNA sequencing (RNA-Seq) measures genome-wide gene expression. RNA-Seq data is count-based rendering normal distribution models for analysis inappropriate. Normalization of RNA-Seq data to transform the data has limitations which can adversely impact the analysis. Furthermore, there are a few count-based methods for analysis of RNA-Seq data but they are essentially for pairwise analysis of treatment groups or multiclasses but not pattern-based to identify co-expressed genes.

Results

We adapted our extracting patterns and identifying genes methodology for RNA-Seq (EPIG-Seq) count data. The software uses count-based correlation to measure similarity between genes, quasi-Poisson modelling to estimate dispersion in the data and a location parameter to indicate magnitu

SUBMITTER: Li J 

PROVIDER: S-EPMC4804494 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature