Using set theory to reduce redundancy in pathway sets.

ABSTRACT:

Background

The consolidation of pathway databases, such as KEGG, Reactome and ConsensusPathDB, has generated widespread biological interest, however the issue of pathway redundancy impedes the use of these consolidated datasets. Attempts to reduce this redundancy have focused on visualizing pathway overlap or merging pathways, but the resulting pathways may be of heterogeneous sizes and cover multiple biological functions. Efforts have also been made to deal with redundancy in pathway data by consolidating enriched pathways into a number of clusters or concepts. We present an alternative approach, which generates pathway subsets capable of covering all of genes presented within either pathway databases or enrichment results, generating substantial reductions in redundancy.

Resul

SUBMITTER: Stoney RA 

PROVIDER: S-EPMC6194563 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature