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SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci
Summary: We created a fast, robust and general C++ implementation of a single-nucleotide polymorphism (SNP) set enrichment algorithm to identify cell types, tissues and pathways affected by risk loci. It tests trait-associated genomic loci for enrichment of specificity to conditions (cell types, tis...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147889/ https://www.ncbi.nlm.nih.gov/pubmed/24813542 http://dx.doi.org/10.1093/bioinformatics/btu326 |
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author | Slowikowski, Kamil Hu, Xinli Raychaudhuri, Soumya |
author_facet | Slowikowski, Kamil Hu, Xinli Raychaudhuri, Soumya |
author_sort | Slowikowski, Kamil |
collection | PubMed |
description | Summary: We created a fast, robust and general C++ implementation of a single-nucleotide polymorphism (SNP) set enrichment algorithm to identify cell types, tissues and pathways affected by risk loci. It tests trait-associated genomic loci for enrichment of specificity to conditions (cell types, tissues and pathways). We use a non-parametric statistical approach to compute empirical P-values by comparison with null SNP sets. As a proof of concept, we present novel applications of our method to four sets of genome-wide significant SNPs associated with red blood cell count, multiple sclerosis, celiac disease and HDL cholesterol. Availability and implementation: http://broadinstitute.org/mpg/snpsea Contact: soumya@broadinstitute.org Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4147889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41478892014-09-02 SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci Slowikowski, Kamil Hu, Xinli Raychaudhuri, Soumya Bioinformatics Applications Notes Summary: We created a fast, robust and general C++ implementation of a single-nucleotide polymorphism (SNP) set enrichment algorithm to identify cell types, tissues and pathways affected by risk loci. It tests trait-associated genomic loci for enrichment of specificity to conditions (cell types, tissues and pathways). We use a non-parametric statistical approach to compute empirical P-values by comparison with null SNP sets. As a proof of concept, we present novel applications of our method to four sets of genome-wide significant SNPs associated with red blood cell count, multiple sclerosis, celiac disease and HDL cholesterol. Availability and implementation: http://broadinstitute.org/mpg/snpsea Contact: soumya@broadinstitute.org Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2014-09-01 2014-05-10 /pmc/articles/PMC4147889/ /pubmed/24813542 http://dx.doi.org/10.1093/bioinformatics/btu326 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), 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 Slowikowski, Kamil Hu, Xinli Raychaudhuri, Soumya SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci |
title | SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci |
title_full | SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci |
title_fullStr | SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci |
title_full_unstemmed | SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci |
title_short | SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci |
title_sort | snpsea: an algorithm to identify cell types, tissues and pathways affected by risk loci |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147889/ https://www.ncbi.nlm.nih.gov/pubmed/24813542 http://dx.doi.org/10.1093/bioinformatics/btu326 |
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