Journal of Computer Science & Systems Biology

Dimitrios V Vavoulis

Publications

• Research Article
  Non-Parametric Bayesian Modelling of Digital Gene Expression Data
  Author(s): Dimitrios V Vavoulis and Julian GoughDimitrios V Vavoulis and Julian Gough
  
  Next-generation sequencing technologies provide a revolutionary tool for generating gene expression data. Starting with a fixed RNA sample, they construct a library of millions of differentially abundant short sequence tags or “reads”, which constitute a fundamentally discrete measure of the level of gene expression. A common limitation in experiments using these technologies is the low number or even absence of biological replicates, which complicates the statistical analysis of digital gene expression data. Analysis of this type of data has often been based on modified tests originally devised for analysing microarrays; both these and even de novo methods for the analysis of RNA-seq data are plagued by the common problem of low replication. We propose a novel, non-parametric Bayesian approach for the analysis of digital gene expression data. .. Read More»
  DOI: 10.4172/jcsb.1000131

  Abstract PDF