Identification of sample-specific regulations using integrative network level analysis.

ABSTRACT:

Background

Histologically similar tumors even from the same anatomical position may still show high variability at molecular level hindering analysis of genome-wide data. Leveling the analysis to a gene regulatory network instead of focusing on single genes has been suggested to overcome the heterogeneity issue although the majority of the network methods require large datasets. Network methods that are able to function at a single sample level are needed to overcome the heterogeneity and sample size issues.

Methods

We present a novel network method, Differentially Expressed Regulation Analysis (DERA) that integrates expression data to biological network information at a single sample level. The sample-specific networks are subsequently used to discover samples with similar

SUBMITTER: Liu C 

PROVIDER: S-EPMC4424448 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature