Abstract
BackgroundBridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy. Approaches that can flexibly and intuitively, integrate known gene-phenotype associations in the context of molecular signaling networks are vital to effectively prioritize and biologically interpret genes underlying disease traits of interest.ResultsWe describe Phenotype Consensus Analysis (PCAN); a method to assess the consensus semantic similarity of phenotypes in a candidate gene’s signaling neighborhood. We demonstrate that significant phenotype consensus (p < 0.05) is observable for ~67% of 4,549 OMIM disease-gene associations, using a combination of high quality String interactions + Metabase pathways and use Joubert Syndrome to demonstrate the ease with which a significant result can be interrogated to highlight discriminatory traits linked to mechanistically related genes.ConclusionsWe advocate phenotype consensus as an intuitive and versatile method to aid disease-gene association, which naturally lends itself to the mechanistic deconvolution of diverse phenotypes. We provide PCAN to the community as an R package (http://bioconductor.org/packages/PCAN/) to allow flexible configuration, extension and standalone use or integration to supplement existing gene prioritization workflows.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1401-2) contains supplementary material, which is available to authorized users.
Highlights
Bridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy
We provide Phenotype Consensus Analysis (PCAN) to the community as an R package, available to download from Bioconductor, to allow integration into existing rare disease variant prioritization workflows and support extensive customization and versatile exploration of the molecular etiology of disease
First all Mendelian disease genes are annotated with standardized trait labels (HP terms) from the Human Phenotype Ontology (HPO) [9] according to the genetic disease or diseases they cause
Summary
Bridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy. Approaches that can flexibly and intuitively, integrate known gene-phenotype associations in the context of molecular signaling networks are vital to effectively prioritize and biologically interpret genes underlying disease traits of interest. That exhibit Mendelian inheritance, provide strong links between genotype and phenotype and individually they affect only a small fraction of the global population, together there are over 3,600 different rare Mendelian diseases associated with over 3,100 different genes. A holistic view of existing Mendelian disease genes will aid the discovery of novel disorders and associated genes but together resolve fundamental molecular mechanisms that give rise to human phenotypic traits of broad therapeutic potential [2, 3]. The final diagnostic coup de grace often comes down to whether other variants in the same gene are known to cause a similar phenotype
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