An efficient algorithm to explore liquid association on a genome-wide scale.

ABSTRACT:

Background

The growing wealth of public available gene expression data has made the systemic studies of how genes interact in a cell become more feasible. Liquid association (LA) describes the extent to which coexpression of two genes may vary based on the expression level of a third gene (the controller gene). However, genome-wide application has been difficult and resource-intensive. We propose a new screening algorithm for more efficient processing of LA estimation on a genome-wide scale and apply its use to a Saccharomyces cerevisiae data set.

Results

On a test subset of the data, the fast screening algorithm achieved >99.8% agreement with the exhaustive search of LA values, while reduced run time by 81-93 %. Using a well-known yeast cell-cycle data set with 6,178 genes,

SUBMITTER: Gunderson T 

PROVIDER: S-EPMC4255454 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature