ArticleBMC bioinformatics2010
An integrative method for scoring candidate genes from association studies: application to warfarin dosing.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Article
- The influence of ethnicity on warfarin dosage requirements in the chilean population.Current therapeutic research, clinical and experimental · 2015Article
- Greater power and computational efficiency for kernel-based association testing of sets of genetic variants.Bioinformatics (Oxford, England) · 2014Article
- PERSONALIZED MEDICINE: FROM GENOTYPES AND MOLECULAR PHENOTYPES TOWARDS COMPUTED THERAPY.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2013Article
- Cancer pharmacogenomics: strategies and challenges.Nature reviews. Genetics · 2013Review
- Pathway analysis of genome-wide data improves warfarin dose prediction.BMC genomics · 2013Article
- Genome wide analysis of drug-induced torsades de pointes: lack of common variants with large effect sizes.PloS one · 2013Article
- Relating human genetic variation to variation in drug responses.Trends in genetics : TIG · 2012Review
- Lymphoblastoid cell lines in pharmacogenomic discovery and clinical translation.Pharmacogenomics · 2012Review
- Chapter 7: Pharmacogenomics.PLoS computational biology · 2012Article
- Selected proceedings of the 2010 Summit on Translational Bioinformatics.BMC bioinformatics · 2010Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundA key challenge in pharmacogenomics is the identification of genes whose variants contribute to drug response phenotypes, which can include severe adverse effects. Pharmacogenomics GWAS attempt to elucidate genotypes predictive of drug response. However, the size of these studies has severely limited their power and potential application. We propose a novel knowledge integration and SNP aggregation approach for identifying genes impacting drug response. Our SNP aggregation method characterizes the degree to which uncommon alleles of a gene are associated with drug response. We first use pre-existing knowledge sources to rank pharmacogenes by their likelihood to affect drug response. We then define a summary score for each gene based on allele frequencies and train linear and logistic regression classifiers to predict drug response phenotypes.
resultsWe applied our method to a published warfarin GWAS data set comprising 181 individuals. We find that our method can increase the power of the GWAS to identify both VKORC1 and CYP2C9 as warfarin pharmacogenes, where the original analysis had only identified VKORC1. Additionally, we find that our method can be used to discriminate between low-dose (AUROC=0.886) and high-dose (AUROC=0.764) responders.
conclusionsOur method offers a new route for candidate pharmacogene discovery from pharmacogenomics GWAS, and serves as a foundation for future work in methods for predictive pharmacogenomics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.