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FeatSNP: An Interactive Database for Brain-Specific Epigenetic Annotation of Human SNPs

FeatSNP is an online tool and a curated database for exploring 81 million common SNPs’ potential functional impact on the human brain. FeatSNP uses the brain transcriptomes of the human population to improve functional annotation of human SNPs by integrating transcription factor binding prediction,...

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Autores principales: Ma, Chun-yu, Madden, Pamela, Gontarz, Paul, Wang, Ting, Zhang, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454007/
https://www.ncbi.nlm.nih.gov/pubmed/31001319
http://dx.doi.org/10.3389/fgene.2019.00262
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author Ma, Chun-yu
Madden, Pamela
Gontarz, Paul
Wang, Ting
Zhang, Bo
author_facet Ma, Chun-yu
Madden, Pamela
Gontarz, Paul
Wang, Ting
Zhang, Bo
author_sort Ma, Chun-yu
collection PubMed
description FeatSNP is an online tool and a curated database for exploring 81 million common SNPs’ potential functional impact on the human brain. FeatSNP uses the brain transcriptomes of the human population to improve functional annotation of human SNPs by integrating transcription factor binding prediction, public eQTL information, and brain specific epigenetic landscape, as well as information of Topologically Associating Domains (TADs). FeatSNP supports both single and batched SNP searching, and its interactive user interface enables users to explore the functional annotations and generate publication-quality visualization results. FeatSNP is freely available on the internet at FeatSNP.org with all major web browsers supported.
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spelling pubmed-64540072019-04-18 FeatSNP: An Interactive Database for Brain-Specific Epigenetic Annotation of Human SNPs Ma, Chun-yu Madden, Pamela Gontarz, Paul Wang, Ting Zhang, Bo Front Genet Genetics FeatSNP is an online tool and a curated database for exploring 81 million common SNPs’ potential functional impact on the human brain. FeatSNP uses the brain transcriptomes of the human population to improve functional annotation of human SNPs by integrating transcription factor binding prediction, public eQTL information, and brain specific epigenetic landscape, as well as information of Topologically Associating Domains (TADs). FeatSNP supports both single and batched SNP searching, and its interactive user interface enables users to explore the functional annotations and generate publication-quality visualization results. FeatSNP is freely available on the internet at FeatSNP.org with all major web browsers supported. Frontiers Media S.A. 2019-04-02 /pmc/articles/PMC6454007/ /pubmed/31001319 http://dx.doi.org/10.3389/fgene.2019.00262 Text en Copyright © 2019 Ma, Madden, Gontarz, Wang and Zhang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Ma, Chun-yu
Madden, Pamela
Gontarz, Paul
Wang, Ting
Zhang, Bo
FeatSNP: An Interactive Database for Brain-Specific Epigenetic Annotation of Human SNPs
title FeatSNP: An Interactive Database for Brain-Specific Epigenetic Annotation of Human SNPs
title_full FeatSNP: An Interactive Database for Brain-Specific Epigenetic Annotation of Human SNPs
title_fullStr FeatSNP: An Interactive Database for Brain-Specific Epigenetic Annotation of Human SNPs
title_full_unstemmed FeatSNP: An Interactive Database for Brain-Specific Epigenetic Annotation of Human SNPs
title_short FeatSNP: An Interactive Database for Brain-Specific Epigenetic Annotation of Human SNPs
title_sort featsnp: an interactive database for brain-specific epigenetic annotation of human snps
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454007/
https://www.ncbi.nlm.nih.gov/pubmed/31001319
http://dx.doi.org/10.3389/fgene.2019.00262
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