Differential analysis of high-throughput quantitative genetic interaction data.
|Title||Differential analysis of high-throughput quantitative genetic interaction data.|
|Publication Type||Journal Article|
|Year of Publication||2012|
|Authors||Bean GJ, Ideker T|
|Date Published||2012 Dec 26|
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.
|Alternate Journal||Genome Biol.|