Prioritization of retinal disease genes: an integrative approach

Alex H Wagner; Kyle R Taylor; Adam P DeLuca; Thomas L Casavant; Robert F Mullins; Edwin M Stone; Todd E Scheetz; Terry A Braun

doi:10.1002/humu.22317

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Prioritization of retinal disease genes: an integrative approach

Journal article

Open access

Peer reviewed

Prioritization of retinal disease genes: an integrative approach

Alex H Wagner, Kyle R Taylor, Adam P DeLuca, Thomas L Casavant, Robert F Mullins, Edwin M Stone, Todd E Scheetz and Terry A Braun

Human mutation, Vol.34(6), pp.853-859

06/2013

DOI: 10.1002/humu.22317

PMCID: PMC4509594

PMID: 23508994

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Abstract

The discovery of novel disease-associated variations in genes is often a daunting task in highly heterogeneous disease classes. We seek a generalizable algorithm that integrates multiple publicly available genomic data sources in a machine-learning model for the prioritization of candidates identified in patients with retinal disease. To approach this problem, we generate a set of feature vectors from publicly available microarray, RNA-seq, and ChIP-seq datasets of biological relevance to retinal disease, to observe patterns in gene expression specificity among tissues of the body and the eye, in addition to photoreceptor-specific signals by the CRX transcription factor. Using these features, we describe a novel algorithm, positive and unlabeled learning for prioritization (PULP). This article compares several popular supervised learning techniques as the regression function for PULP. The results demonstrate a highly significant enrichment for previously characterized disease genes using a logistic regression method. Finally, a comparison of PULP with the popular gene prioritization tool ENDEAVOUR shows superior prioritization of retinal disease genes from previous studies. The java source code, compiled binary, assembled feature vectors, and instructions are available online at https://github.com/ahwagner/PULP.

Retinal Diseases - genetics

Computational Biology - methods

Reproducibility of Results

Algorithms

Animals

Genetic Association Studies

Artificial Intelligence

Humans

Mice

Software

Internet

Genomics - methods

Details

Title: Subtitle: Prioritization of retinal disease genes: an integrative approach
Creators: Alex H Wagner - Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa 52242, USA. alex-wagner@uiowa.edu
Kyle R Taylor
Adam P DeLuca
Thomas L Casavant
Robert F Mullins
Edwin M Stone
Todd E Scheetz
Terry A Braun
Resource Type: Journal article
Publication Details: Human mutation, Vol.34(6), pp.853-859
DOI: 10.1002/humu.22317
PMID: 23508994
PMCID: PMC4509594
NLM abbreviation: Hum Mutat
ISSN: 1059-7794
eISSN: 1098-1004
Publisher: United States
Grant note: T32 GM008629 / NIGMS NIH HHS T32 GM082729 / NIGMS NIH HHS T32GM082729 / NIGMS NIH HHS
Language: English
Date published: 06/2013
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Iowa Neuroscience Institute; Center for Bioinformatics and Computational Biology; Ophthalmology and Visual Sciences
Record Identifier: 9983980055902771

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