ArticleHuman mutation2011
Prediction of functional regulatory SNPs in monogenic and complex disease.
Article in Human mutation, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Variation benchmark datasets: update, criteria, quality and applications.Database : the journal of biological databases and curation · 2020Article
- CERENKOV3: Clustering and molecular network-derived features improve computational prediction of functional noncoding SNPs.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2020Article
- CERENKOV2: improved detection of functional noncoding SNPs using data-space geometric features.BMC bioinformatics · 2019Article
- Novel functional variants at the GWAS-implicated loci might confer risk to major depressive disorder, bipolar affective disorder and schizophrenia.BMC neuroscience · 2018Article
- Regulatory single nucleotide polymorphisms (rSNPs) at the promoters 1A and 1B of the human APC gene.BMC genetics · 2016Article
- Regulatory Single-Nucleotide Variant Predictor Increases Predictive Performance of Functional Regulatory Variants.Human mutation · 2016Article
- Review
- Progress towards the integration of pharmacogenomics in practice.Human genetics · 2015Review
- Exploring functional variant discovery in non-coding regions with SInBaD.Nucleic acids research · 2013Article
- Article
- An excess of deleterious variants in VEGF-A pathway genes in Down-syndrome-associated atrioventricular septal defects.American journal of human genetics · 2012Article
- Bioinformatics for personal genome interpretation.Briefings in bioinformatics · 2012Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Next-generation sequencing (NGS) technologies are yielding ever higher volumes of human genome sequence data. Given this large amount of data, it has become both a possibility and a priority to determine how disease-causing single nucleotide polymorphisms (SNPs) detected within gene regulatory regions (rSNPs) exert their effects on gene expression. Recently, several studies have explored whether disease-causing polymorphisms have attributes that can distinguish them from those that are neutral, attaining moderate success at discriminating between functional and putatively neutral regulatory SNPs. Here, we have extended this work by assessing the utility of both SNP-based features (those associated only with the polymorphism site and the surrounding DNA) and gene-based features (those derived from the associated gene in whose regulatory region the SNP lies) in the identification of functional regulatory polymorphisms involved in either monogenic or complex disease. Gene-based features were found to be capable of both augmenting and enhancing the utility of SNP-based features in the prediction of known regulatory mutations. Adopting this approach, we achieved an AUC of 0.903 for predicting regulatory SNPs. Finally, our tool predicted 225 new regulatory SNPs with a high degree of confidence, with 105 of the 225 falling into linkage disequilibrium blocks of reported disease-associated genome-wide association studies SNPs.
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Registered trials
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