ArticleBioinformatics (Oxford, England)2009
A multi-dimensional evidence-based candidate gene prioritization approach for complex diseases-schizophrenia as a case.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 2 of them syntheses that pooled it.
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Who cites it
50 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Systematic prioritization and integrative analysis of copy number variations in schizophrenia reveal key schizophrenia susceptibility genes.Schizophrenia bulletin · 2014Pooled it
- GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia.Molecular psychiatry · 2011Pooled it
- Bioinformatic Analysis of Genetic Factors from Human Blood Samples and Postmortem Brains in Parkinson's Disease.Oxidative medicine and cellular longevity · 2022Article
- Prioritizing Suggestive Candidate Genes in Migraine: An Opinion.Frontiers in neurology · 2022Article
- Genetic Modifiers at the Crossroads of Personalised Medicine for Haemoglobinopathies.Journal of clinical medicine · 2019Article
- Mega-analysis of Odds Ratio: A Convergent Method for a Deep Understanding of the Genetic Evidence in Schizophrenia.Schizophrenia bulletin · 2019Article
- Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach.Scientific reports · 2018Article
- AutismKB 2.0: a knowledgebase for the genetic evidence of autism spectrum disorder.Database : the journal of biological databases and curation · 2018Article
- Evidence-based prioritisation and enrichment of genes interacting with metformin in type 2 diabetes.Diabetologia · 2017Article
- Gene Prioritization by Compressive Data Fusion and Chaining.PLoS computational biology · 2015Article
- Laminar and dorsoventral molecular organization of the medial entorhinal cortex revealed by large-scale anatomical analysis of gene expression.PLoS computational biology · 2015Article
- A weighted and integrated drug-target interactome: drug repurposing for schizophrenia as a use case.BMC systems biology · 2015Article
- Guilt by rewiring: gene prioritization through network rewiring in genome wide association studies.Human molecular genetics · 2014Article
- Combinatorial therapy discovery using mixed integer linear programming.Bioinformatics (Oxford, England) · 2014Article
- Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease.BMC genomics · 2014Article
- Neurodevelopmental and neuropsychiatric disorders represent an interconnected molecular system.Molecular psychiatry · 2014Article
- Network.assisted analysis to prioritize GWAS results: principles, methods and perspectives.Human genetics · 2014Review
- Evolutionary conservation in genes underlying human psychiatric disorders.Frontiers in human neuroscience · 2014Article
- Network-assisted prediction of potential drugs for addiction.BioMed research international · 2014Article
- Association study of 83 candidate genes for bipolar disorder in chromosome 6q selected using an evidence-based prioritization algorithm.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2013Article
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9 authors.
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Abstract
motivationDuring the past decade, we have seen an exponential growth of vast amounts of genetic data generated for complex disease studies. Currently, across a variety of complex biological problems, there is a strong trend towards the integration of data from multiple sources. So far, candidate gene prioritization approaches have been designed for specific purposes, by utilizing only some of the available sources of genetic studies, or by using a simple weight scheme. Specifically to psychiatric disorders, there has been no prioritization approach that fully utilizes all major sources of experimental data.
resultsHere we present a multi-dimensional evidence-based candidate gene prioritization approach for complex diseases and demonstrate it in schizophrenia. In this approach, we first collect and curate genetic studies for schizophrenia from four major categories: association studies, linkage analyses, gene expression and literature search. Genes in these data sets are initially scored by category-specific scoring methods. Then, an optimal weight matrix is searched by a two-step procedure (core genes and unbiased P-values in independent genome-wide association studies). Finally, genes are prioritized by their combined scores using the optimal weight matrix. Our evaluation suggests this approach generates prioritized candidate genes that are promising for further analysis or replication. The approach can be applied to other complex diseases. AVAILABILITY: The collected data, prioritized candidate genes, and gene prioritization tools are freely available at http://bioinfo.mc.vanderbilt.edu/SZGR/.
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