Title: Differential analysis of high-throughput quantitative genetic interaction data.
Authors: Bean, Gordon J; Ideker, Trey
Published In Genome Biol, (2012 Dec 26)
Abstract: Synthetic genetic arrays have been very effective at measuring genetic interactions in yeast in a high-throughput manner and recently have been expanded to measure quantitative changes in interaction, termed 'differential interactions', across multiple conditions. Here, we present a strategy that leverages statistical information from the experimental design to produce a novel, quantitative differential interaction score, which performs favorably compared to previous differential scores. We also discuss the added utility of differential genetic-similarity in differential network analysis. Our approach is preferred for differential network analysis, and our implementation, written in MATLAB, can be found at http://chianti.ucsd.edu/~gbean/compute_differential_scores.m.
PubMed ID: 23268787
MeSH Terms: Data Interpretation, Statistical; Epistasis, Genetic; Gene Regulatory Networks*; Genetic Techniques; Models, Genetic; Mutation; Yeasts/genetics