Flaherty P, et al. (2005) A latent variable model for chemogenomic profiling. Bioinformatics 21(15):3286-93
Abstract: MOTIVATION: In haploinsufficiency profiling (HIP) data (Giaever et al., 2002), 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. RESULTS: We applied our model to the clustering of 79 chemogenomic experiments in yeast. Known pleiotropic genes PDR5 and MAL11 are more accurately represented by the model than by a clustering procedure that requires genes to belong to a single cluster. Drugs such as miconazole and fenpropimorph that have different targets but similar off-target genes are clustered more accurately by the model-based framework. We show that this model is useful for summarizing the relationship among treatments and genes affected by those treatments in a compendium of microarray profiles. AVAILABILITY: Supplementary information and computer code at http://genomics.lbl.gov/~patrickf/llda.html.
|Status: Published||Type: Journal Article||PubMed ID: 15919724|
Topics addressed in this paper
Number of different genes curated to this paper: 30
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