Background: New technology has resulted in high-throughput screens for
pairwise genetic interactions in yeast and other model organisms. For each pair in a
collection of non-essential genes, an epistasis score is obtained, representing how
much sicker (or healthier) the double-knockout organism will be compared to what
would be expected f... read morerom the sickness of the component single knockouts. Recent
algorithmic work has identified graph-theoretic patterns in this data that can
indicate functional modules, and even sets of genes that may occur in compensatory
pathways, such as a BPM-type schema first introduced by Kelley and Ideker. However,
to date, any algorithms for finding such patterns in the data were implemented
internally, with no software being made publically available.
Gallant, Andrew, Mark DM Leiserson, Maxim Kachalov, Lenore J.
Cowen, and Benjamin J. Hescott. "Genecentric: a package to uncover graph-theoretic
structure in high-throughput epistasis data." BMC Bioinformatics 14, no. 1 (12,