Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study.

ABSTRACT:

Background

In genomics, highly relevant gene interaction (co-expression) networks have been constructed by finding significant pair-wise correlations between genes in expression datasets. These networks are then mined to elucidate biological function at the polygenic level. In some cases networks may be constructed from input samples that measure gene expression under a variety of different conditions, such as for different genotypes, environments, disease states and tissues. When large sets of samples are obtained from public repositories it is often unmanageable to associate samples into condition-specific groups, and combining samples from various conditions has a negative effect on network size. A fixed significance threshold is often applied also limiting the size of the final

SUBMITTER: Feltus FA 

PROVIDER: S-EPMC3679940 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature