TY - JOUR T1 - Not by systems alone: identifying functional outliers in rare disease pedigrees JF - bioRxiv DO - 10.1101/128439 SP - 128439 AU - Sara Ballouz AU - Max Dörfel AU - Jonathan Crain AU - Megan Crow AU - Laurence Faivre AU - Catherine E. Keegan AU - Sophia Kitsiou-Tzeli AU - Maria Tzetis AU - Gholson J. Lyon AU - Jesse Gillis Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/04/18/128439.abstract N2 - In disease expression analysis, looking for shared functional signals from a set of genes which exhibit differential expression is commonplace. We examine the complement as a possibility, that disease genes display “outlier” or unexpected expression relative to broader patterns of functional expression variation. Using six families from the rare TAF1 syndrome disease cohort, we performed family-specific differential expression analyses and find that functional characterization of top candidates enriches for common pathways unlikely to be specifically linked to disease. However, by filtering away common expression changes using known co-expression, we lose all functional enrichment and are left with a small number of outliers characteristic of each proband. Two of these outlier genes are highly recurrent across pedigrees (FDR <2.63e-05) and are the primary commonality among the cohort as a whole. This suggests that systems analysis may be relevant to rare diseases principally as a means of filtering out biological signals unrelated to disease.ROCReceiver Operating CharacteristicAUROCArea Under the ROCDEDifferential ExpressionFDRFalse Discovery Rate (Benjamini-Hochberg correction)FWERFamily-Wise Error Rate (Bonferroni correction)GOGene ontologyCPMCounts Per Million (relative RNA expression based on read counts) ER -