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JEPEGMIX: gene-level joint analysis of functional SNPs in cosmopolitan cohorts
Motivation: To increase detection power, gene level analysis methods are used to aggregate weak signals. To greatly increase computational efficiency, most methods use as input summary statistics from genome-wide association studies (GWAS). Subsequently, gene statistics are constructed using linkage...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4708106/ https://www.ncbi.nlm.nih.gov/pubmed/26428293 http://dx.doi.org/10.1093/bioinformatics/btv567 |
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author | Lee, Donghyung Williamson, Vernell S. Bigdeli, T. Bernard Riley, Brien P. Webb, Bradley T. Fanous, Ayman H. Kendler, Kenneth S. Vladimirov, Vladimir I. Bacanu, Silviu-Alin |
author_facet | Lee, Donghyung Williamson, Vernell S. Bigdeli, T. Bernard Riley, Brien P. Webb, Bradley T. Fanous, Ayman H. Kendler, Kenneth S. Vladimirov, Vladimir I. Bacanu, Silviu-Alin |
author_sort | Lee, Donghyung |
collection | PubMed |
description | Motivation: To increase detection power, gene level analysis methods are used to aggregate weak signals. To greatly increase computational efficiency, most methods use as input summary statistics from genome-wide association studies (GWAS). Subsequently, gene statistics are constructed using linkage disequilibrium (LD) patterns from a relevant reference panel. However, all methods, including our own Joint Effect on Phenotype of eQTL/functional single nucleotide polymorphisms (SNPs) associated with a Gene (JEPEG), assume homogeneous panels, e.g. European. However, this renders these tools unsuitable for the analysis of large cosmopolitan cohorts. Results: We propose a JEPEG extension, JEPEGMIX, which similar to one of our software tools, Direct Imputation of summary STatistics of unmeasured SNPs from MIXed ethnicity cohorts, is capable of estimating accurate LD patterns for cosmopolitan cohorts. JEPEGMIX uses this accurate LD estimates to (i) impute the summary statistics at unmeasured functional variants and (ii) test for the joint effect of all measured and imputed functional variants which are associated with a gene. We illustrate the performance of our tool by analyzing the GWAS meta-analysis summary statistics from the multi-ethnic Psychiatric Genomics Consortium Schizophrenia stage 2 cohort. This practical application supports the immune system being one of the main drivers of the process leading to schizophrenia. Availability and implementation: Software, annotation database and examples are available at http://dleelab.github.io/jepegmix/. Contact: donghyung.lee@vcuhealth.org Supplementary information: Supplementary material is available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4708106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47081062016-01-12 JEPEGMIX: gene-level joint analysis of functional SNPs in cosmopolitan cohorts Lee, Donghyung Williamson, Vernell S. Bigdeli, T. Bernard Riley, Brien P. Webb, Bradley T. Fanous, Ayman H. Kendler, Kenneth S. Vladimirov, Vladimir I. Bacanu, Silviu-Alin Bioinformatics Applications Notes Motivation: To increase detection power, gene level analysis methods are used to aggregate weak signals. To greatly increase computational efficiency, most methods use as input summary statistics from genome-wide association studies (GWAS). Subsequently, gene statistics are constructed using linkage disequilibrium (LD) patterns from a relevant reference panel. However, all methods, including our own Joint Effect on Phenotype of eQTL/functional single nucleotide polymorphisms (SNPs) associated with a Gene (JEPEG), assume homogeneous panels, e.g. European. However, this renders these tools unsuitable for the analysis of large cosmopolitan cohorts. Results: We propose a JEPEG extension, JEPEGMIX, which similar to one of our software tools, Direct Imputation of summary STatistics of unmeasured SNPs from MIXed ethnicity cohorts, is capable of estimating accurate LD patterns for cosmopolitan cohorts. JEPEGMIX uses this accurate LD estimates to (i) impute the summary statistics at unmeasured functional variants and (ii) test for the joint effect of all measured and imputed functional variants which are associated with a gene. We illustrate the performance of our tool by analyzing the GWAS meta-analysis summary statistics from the multi-ethnic Psychiatric Genomics Consortium Schizophrenia stage 2 cohort. This practical application supports the immune system being one of the main drivers of the process leading to schizophrenia. Availability and implementation: Software, annotation database and examples are available at http://dleelab.github.io/jepegmix/. Contact: donghyung.lee@vcuhealth.org Supplementary information: Supplementary material is available at Bioinformatics online. Oxford University Press 2016-01-15 2015-10-01 /pmc/articles/PMC4708106/ /pubmed/26428293 http://dx.doi.org/10.1093/bioinformatics/btv567 Text en © The Author 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Lee, Donghyung Williamson, Vernell S. Bigdeli, T. Bernard Riley, Brien P. Webb, Bradley T. Fanous, Ayman H. Kendler, Kenneth S. Vladimirov, Vladimir I. Bacanu, Silviu-Alin JEPEGMIX: gene-level joint analysis of functional SNPs in cosmopolitan cohorts |
title | JEPEGMIX: gene-level joint analysis of functional SNPs in cosmopolitan cohorts |
title_full | JEPEGMIX: gene-level joint analysis of functional SNPs in cosmopolitan cohorts |
title_fullStr | JEPEGMIX: gene-level joint analysis of functional SNPs in cosmopolitan cohorts |
title_full_unstemmed | JEPEGMIX: gene-level joint analysis of functional SNPs in cosmopolitan cohorts |
title_short | JEPEGMIX: gene-level joint analysis of functional SNPs in cosmopolitan cohorts |
title_sort | jepegmix: gene-level joint analysis of functional snps in cosmopolitan cohorts |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4708106/ https://www.ncbi.nlm.nih.gov/pubmed/26428293 http://dx.doi.org/10.1093/bioinformatics/btv567 |
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