A latent variable model for chemogenomic profiling

Patrick Flaherty, Guri Giaever, Jochen Kumm, Michael I. Jordan, Adam P. Arkin

Abstract: In haploinsufficiency profiling data, pleiotropic genes are often misclassified by clustering algorithms that impose the constraint that a gene or experiment belong to only one cluster. We have developed a general probabilistic model that clusters genes and experiments without requiring that a given gene or drug only appear in one cluster. The model also incorporates the functional annotation of known genes to guide the clustering procedure.