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HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models
Models of transcription factor (TF) binding sites provide a basis for a wide spectrum of studies in regulatory genomics, from reconstruction of regulatory networks to functional annotation of transcripts and sequence variants. While TFs may recognize different sequence patterns in different conditio...
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/PMC4702883/ https://www.ncbi.nlm.nih.gov/pubmed/26586801 http://dx.doi.org/10.1093/nar/gkv1249 |
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author | Kulakovskiy, Ivan V. Vorontsov, Ilya E. Yevshin, Ivan S. Soboleva, Anastasiia V. Kasianov, Artem S. Ashoor, Haitham Ba-alawi, Wail Bajic, Vladimir B. Medvedeva, Yulia A. Kolpakov, Fedor A. Makeev, Vsevolod J. |
author_facet | Kulakovskiy, Ivan V. Vorontsov, Ilya E. Yevshin, Ivan S. Soboleva, Anastasiia V. Kasianov, Artem S. Ashoor, Haitham Ba-alawi, Wail Bajic, Vladimir B. Medvedeva, Yulia A. Kolpakov, Fedor A. Makeev, Vsevolod J. |
author_sort | Kulakovskiy, Ivan V. |
collection | PubMed |
description | Models of transcription factor (TF) binding sites provide a basis for a wide spectrum of studies in regulatory genomics, from reconstruction of regulatory networks to functional annotation of transcripts and sequence variants. While TFs may recognize different sequence patterns in different conditions, it is pragmatic to have a single generic model for each particular TF as a baseline for practical applications. Here we present the expanded and enhanced version of HOCOMOCO (http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco10), the collection of models of DNA patterns, recognized by transcription factors. HOCOMOCO now provides position weight matrix (PWM) models for binding sites of 601 human TFs and, in addition, PWMs for 396 mouse TFs. Furthermore, we introduce the largest up to date collection of dinucleotide PWM models for 86 (52) human (mouse) TFs. The update is based on the analysis of massive ChIP-Seq and HT-SELEX datasets, with the validation of the resulting models on in vivo data. To facilitate a practical application, all HOCOMOCO models are linked to gene and protein databases (Entrez Gene, HGNC, UniProt) and accompanied by precomputed score thresholds. Finally, we provide command-line tools for PWM and diPWM threshold estimation and motif finding in nucleotide sequences. |
format | Online Article Text |
id | pubmed-4702883 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47028832016-01-07 HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models Kulakovskiy, Ivan V. Vorontsov, Ilya E. Yevshin, Ivan S. Soboleva, Anastasiia V. Kasianov, Artem S. Ashoor, Haitham Ba-alawi, Wail Bajic, Vladimir B. Medvedeva, Yulia A. Kolpakov, Fedor A. Makeev, Vsevolod J. Nucleic Acids Res Database Issue Models of transcription factor (TF) binding sites provide a basis for a wide spectrum of studies in regulatory genomics, from reconstruction of regulatory networks to functional annotation of transcripts and sequence variants. While TFs may recognize different sequence patterns in different conditions, it is pragmatic to have a single generic model for each particular TF as a baseline for practical applications. Here we present the expanded and enhanced version of HOCOMOCO (http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco10), the collection of models of DNA patterns, recognized by transcription factors. HOCOMOCO now provides position weight matrix (PWM) models for binding sites of 601 human TFs and, in addition, PWMs for 396 mouse TFs. Furthermore, we introduce the largest up to date collection of dinucleotide PWM models for 86 (52) human (mouse) TFs. The update is based on the analysis of massive ChIP-Seq and HT-SELEX datasets, with the validation of the resulting models on in vivo data. To facilitate a practical application, all HOCOMOCO models are linked to gene and protein databases (Entrez Gene, HGNC, UniProt) and accompanied by precomputed score thresholds. Finally, we provide command-line tools for PWM and diPWM threshold estimation and motif finding in nucleotide sequences. Oxford University Press 2016-01-04 2015-11-19 /pmc/articles/PMC4702883/ /pubmed/26586801 http://dx.doi.org/10.1093/nar/gkv1249 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution 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 | Database Issue Kulakovskiy, Ivan V. Vorontsov, Ilya E. Yevshin, Ivan S. Soboleva, Anastasiia V. Kasianov, Artem S. Ashoor, Haitham Ba-alawi, Wail Bajic, Vladimir B. Medvedeva, Yulia A. Kolpakov, Fedor A. Makeev, Vsevolod J. HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models |
title | HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models |
title_full | HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models |
title_fullStr | HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models |
title_full_unstemmed | HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models |
title_short | HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models |
title_sort | hocomoco: expansion and enhancement of the collection of transcription factor binding sites models |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702883/ https://www.ncbi.nlm.nih.gov/pubmed/26586801 http://dx.doi.org/10.1093/nar/gkv1249 |
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