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DIVAN: accurate identification of non-coding disease-specific risk variants using multi-omics profiles
Understanding the link between non-coding sequence variants, identified in genome-wide association studies, and the pathophysiology of complex diseases remains challenging due to a lack of annotations in non-coding regions. To overcome this, we developed DIVAN, a novel feature selection and ensemble...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5139035/ https://www.ncbi.nlm.nih.gov/pubmed/27923386 http://dx.doi.org/10.1186/s13059-016-1112-z |
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author | Chen, Li Jin, Peng Qin, Zhaohui S. |
author_facet | Chen, Li Jin, Peng Qin, Zhaohui S. |
author_sort | Chen, Li |
collection | PubMed |
description | Understanding the link between non-coding sequence variants, identified in genome-wide association studies, and the pathophysiology of complex diseases remains challenging due to a lack of annotations in non-coding regions. To overcome this, we developed DIVAN, a novel feature selection and ensemble learning framework, which identifies disease-specific risk variants by leveraging a comprehensive collection of genome-wide epigenomic profiles across cell types and factors, along with other static genomic features. DIVAN accurately and robustly recognizes non-coding disease-specific risk variants under multiple testing scenarios; among all the features, histone marks, especially those marks associated with repressed chromatin, are often more informative than others. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-1112-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5139035 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-51390352016-12-15 DIVAN: accurate identification of non-coding disease-specific risk variants using multi-omics profiles Chen, Li Jin, Peng Qin, Zhaohui S. Genome Biol Method Understanding the link between non-coding sequence variants, identified in genome-wide association studies, and the pathophysiology of complex diseases remains challenging due to a lack of annotations in non-coding regions. To overcome this, we developed DIVAN, a novel feature selection and ensemble learning framework, which identifies disease-specific risk variants by leveraging a comprehensive collection of genome-wide epigenomic profiles across cell types and factors, along with other static genomic features. DIVAN accurately and robustly recognizes non-coding disease-specific risk variants under multiple testing scenarios; among all the features, histone marks, especially those marks associated with repressed chromatin, are often more informative than others. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-1112-z) contains supplementary material, which is available to authorized users. BioMed Central 2016-12-06 /pmc/articles/PMC5139035/ /pubmed/27923386 http://dx.doi.org/10.1186/s13059-016-1112-z Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Method Chen, Li Jin, Peng Qin, Zhaohui S. DIVAN: accurate identification of non-coding disease-specific risk variants using multi-omics profiles |
title | DIVAN: accurate identification of non-coding disease-specific risk variants using multi-omics profiles |
title_full | DIVAN: accurate identification of non-coding disease-specific risk variants using multi-omics profiles |
title_fullStr | DIVAN: accurate identification of non-coding disease-specific risk variants using multi-omics profiles |
title_full_unstemmed | DIVAN: accurate identification of non-coding disease-specific risk variants using multi-omics profiles |
title_short | DIVAN: accurate identification of non-coding disease-specific risk variants using multi-omics profiles |
title_sort | divan: accurate identification of non-coding disease-specific risk variants using multi-omics profiles |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5139035/ https://www.ncbi.nlm.nih.gov/pubmed/27923386 http://dx.doi.org/10.1186/s13059-016-1112-z |
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