The characteristic direction: a geometrical approach to identify differentially expressed genes.

ABSTRACT:

Background

Identifying differentially expressed genes (DEG) is a fundamental step in studies that perform genome wide expression profiling. Typically, DEG are identified by univariate approaches such as Significance Analysis of Microarrays (SAM) or Linear Models for Microarray Data (LIMMA) for processing cDNA microarrays, and differential gene expression analysis based on the negative binomial distribution (DESeq) or Empirical analysis of Digital Gene Expression data in R (edgeR) for RNA-seq profiling.

Results

Here we present a new geometrical multivariate approach to identify DEG called the Characteristic Direction. We demonstrate that the Characteristic Direction method is significantly more sensitive than existing methods for identifying DEG in the context of transcriptio

SUBMITTER: Clark NR 

PROVIDER: S-EPMC4000056 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature