Comparing the Efficacy of SNP Filtering Methods for Identifying a Single Causal SNP in a Known Association Region
Genome-wide association studies have successfully identified associations between common diseases and a large number of single nucleotide polymorphisms (SNPs) across the genome. We investigate the effectiveness of several statistics, including p-values, likelihoods, genetic map distance and linkage...
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| Format: | Online |
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BlackWell Publishing Ltd
2014
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4282378/ |
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pubmed-42823782015-01-15 Comparing the Efficacy of SNP Filtering Methods for Identifying a Single Causal SNP in a Known Association Region Spencer, Amy Victoria Cox, Angela Walters, Kevin Original Articles Genome-wide association studies have successfully identified associations between common diseases and a large number of single nucleotide polymorphisms (SNPs) across the genome. We investigate the effectiveness of several statistics, including p-values, likelihoods, genetic map distance and linkage disequilibrium between SNPs, in filtering SNPs in several disease-associated regions. We use simulated data to compare the efficacy of filters with different sample sizes and for causal SNPs with different minor allele frequencies (MAFs) and effect sizes, focusing on the small effect sizes and MAFs likely to represent the majority of unidentified causal SNPs. In our analyses, of all the methods investigated, filtering on the ranked likelihoods consistently retains the true causal SNP with the highest probability for a given false positive rate. This was the case for all the local linkage disequilibrium patterns investigated. Our results indicate that when using this method to retain only the top 5% of SNPs, even a causal SNP with an odds ratio of 1.1 and MAF of 0.08 can be retained with a probability exceeding 0.9 using an overall sample size of 50,000. BlackWell Publishing Ltd 2014-01 2013-11-11 /pmc/articles/PMC4282378/ /pubmed/24205929 http://dx.doi.org/10.1111/ahg.12043 Text en © 2013 The Authors. Annals of Human Genetics published by John Wiley & Sons Ltd/University College London (UCL). http://creativecommons.org/licenses/by/3.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Spencer, Amy Victoria Cox, Angela Walters, Kevin |
| spellingShingle |
Spencer, Amy Victoria Cox, Angela Walters, Kevin Comparing the Efficacy of SNP Filtering Methods for Identifying a Single Causal SNP in a Known Association Region |
| author_facet |
Spencer, Amy Victoria Cox, Angela Walters, Kevin |
| author_sort |
Spencer, Amy Victoria |
| title |
Comparing the Efficacy of SNP Filtering Methods for Identifying a Single Causal SNP in a Known Association Region |
| title_short |
Comparing the Efficacy of SNP Filtering Methods for Identifying a Single Causal SNP in a Known Association Region |
| title_full |
Comparing the Efficacy of SNP Filtering Methods for Identifying a Single Causal SNP in a Known Association Region |
| title_fullStr |
Comparing the Efficacy of SNP Filtering Methods for Identifying a Single Causal SNP in a Known Association Region |
| title_full_unstemmed |
Comparing the Efficacy of SNP Filtering Methods for Identifying a Single Causal SNP in a Known Association Region |
| title_sort |
comparing the efficacy of snp filtering methods for identifying a single causal snp in a known association region |
| description |
Genome-wide association studies have successfully identified associations between common diseases and a large number of single nucleotide polymorphisms (SNPs) across the genome. We investigate the effectiveness of several statistics, including p-values, likelihoods, genetic map distance and linkage disequilibrium between SNPs, in filtering SNPs in several disease-associated regions. We use simulated data to compare the efficacy of filters with different sample sizes and for causal SNPs with different minor allele frequencies (MAFs) and effect sizes, focusing on the small effect sizes and MAFs likely to represent the majority of unidentified causal SNPs. In our analyses, of all the methods investigated, filtering on the ranked likelihoods consistently retains the true causal SNP with the highest probability for a given false positive rate. This was the case for all the local linkage disequilibrium patterns investigated. Our results indicate that when using this method to retain only the top 5% of SNPs, even a causal SNP with an odds ratio of 1.1 and MAF of 0.08 can be retained with a probability exceeding 0.9 using an overall sample size of 50,000. |
| publisher |
BlackWell Publishing Ltd |
| publishDate |
2014 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4282378/ |
| _version_ |
1613172707143188480 |