Bean GJ and Ideker T (2012) Differential analysis of high-throughput quantitative genetic interaction data. Genome Biol 13(12):R123
Abstract: ABSTRACT: Synthetic genetic arrays (SGA) 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.
| Status: Epub ahead of print | Type: Journal Article | PubMed ID: 23268787 |



