PPARα signature development/characterization and screening of a mouse liver gene expression compendium.

<p>Left, signature development and characterization. Wild-type and PPARα-null mice were treated with fenofibrate (Feno) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112655#pone.0112655.ref021" target="_blank">21</a>], perfluorohexanesulfonate (PFHxS) (GSE55756), or WY-14,643 (WY) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112655#pone.0112655.ref022" target="_blank">22</a>] in separate experiments carried out in three different labs. Differentially expressed genes (DEGs) were identified using Rosetta Resolver as indicated. Signature genes were identified from the DEGs after applying a number of filtering steps. Genes in the signature were evaluated by Ingenuity Pathway Analysis (IPA) for canonical pathway enrichment and potential transcription factor regulators and by the Comparative Toxicogenomics Database (CTD) to evaluate literature evidence for consistent regulation of signature genes by PPARα activators. Right, signature testing and screening. The PPARα signature was imported into the NextBio environment in which internal protocols rank ordered the genes based on their fold-change. Screening was carried out by comparison of the signature to each bioset using a pair-wise rank-based enrichment analysis (the Running Fishers algorithm). The results of the test including the direction of correlation and p-value for each bioset in the compendium were exported and used to populate a master table containing bioset experimental details. A test of the accuracy of the signature predictions was carried out with treatments that are known positives and negatives for PPARα activation. Screening “hits” were characterized, and a number of predictions were tested in independent studies. Additionally, an external gene expression database of experiments using Affymetrix gene chips was used in a machine learning classification analysis by BRB Array Tools, principal components analysis (PCA), and examination of the relationships between p-value and gene behavior. Part of the figure was adapted from a figure in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112655#pone.0112655.ref027" target="_blank">27</a>].