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Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data
We developed Lisa (http://lisa.cistrome.org/) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on the input gene sets, Lisa first uses histone mark ChIP-seq and chromatin accessibility profiles to construct a chromatin model related to the...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007693/ https://www.ncbi.nlm.nih.gov/pubmed/32033573 http://dx.doi.org/10.1186/s13059-020-1934-6 |
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author | Qin, Qian Fan, Jingyu Zheng, Rongbin Wan, Changxin Mei, Shenglin Wu, Qiu Sun, Hanfei Brown, Myles Zhang, Jing Meyer, Clifford A. Liu, X. Shirley |
author_facet | Qin, Qian Fan, Jingyu Zheng, Rongbin Wan, Changxin Mei, Shenglin Wu, Qiu Sun, Hanfei Brown, Myles Zhang, Jing Meyer, Clifford A. Liu, X. Shirley |
author_sort | Qin, Qian |
collection | PubMed |
description | We developed Lisa (http://lisa.cistrome.org/) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on the input gene sets, Lisa first uses histone mark ChIP-seq and chromatin accessibility profiles to construct a chromatin model related to the regulation of these genes. Using TR ChIP-seq peaks or imputed TR binding sites, Lisa probes the chromatin models using in silico deletion to find the most relevant TRs. Applied to gene sets derived from targeted TF perturbation experiments, Lisa boosted the performance of imputed TR cistromes and outperformed alternative methods in identifying the perturbed TRs. |
format | Online Article Text |
id | pubmed-7007693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70076932020-02-13 Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data Qin, Qian Fan, Jingyu Zheng, Rongbin Wan, Changxin Mei, Shenglin Wu, Qiu Sun, Hanfei Brown, Myles Zhang, Jing Meyer, Clifford A. Liu, X. Shirley Genome Biol Method We developed Lisa (http://lisa.cistrome.org/) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on the input gene sets, Lisa first uses histone mark ChIP-seq and chromatin accessibility profiles to construct a chromatin model related to the regulation of these genes. Using TR ChIP-seq peaks or imputed TR binding sites, Lisa probes the chromatin models using in silico deletion to find the most relevant TRs. Applied to gene sets derived from targeted TF perturbation experiments, Lisa boosted the performance of imputed TR cistromes and outperformed alternative methods in identifying the perturbed TRs. BioMed Central 2020-02-07 /pmc/articles/PMC7007693/ /pubmed/32033573 http://dx.doi.org/10.1186/s13059-020-1934-6 Text en © The Author(s). 2020 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 Qin, Qian Fan, Jingyu Zheng, Rongbin Wan, Changxin Mei, Shenglin Wu, Qiu Sun, Hanfei Brown, Myles Zhang, Jing Meyer, Clifford A. Liu, X. Shirley Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data |
title | Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data |
title_full | Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data |
title_fullStr | Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data |
title_full_unstemmed | Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data |
title_short | Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data |
title_sort | lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and chip-seq data |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007693/ https://www.ncbi.nlm.nih.gov/pubmed/32033573 http://dx.doi.org/10.1186/s13059-020-1934-6 |
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