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Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling
BACKGROUND: CUT&RUN is an efficient epigenome profiling method that identifies sites of DNA binding protein enrichment genome-wide with high signal to noise and low sequencing requirements. Currently, the analysis of CUT&RUN data is complicated by its exceptionally low background, which rend...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624997/ https://www.ncbi.nlm.nih.gov/pubmed/31300027 http://dx.doi.org/10.1186/s13072-019-0287-4 |
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author | Meers, Michael P. Tenenbaum, Dan Henikoff, Steven |
author_facet | Meers, Michael P. Tenenbaum, Dan Henikoff, Steven |
author_sort | Meers, Michael P. |
collection | PubMed |
description | BACKGROUND: CUT&RUN is an efficient epigenome profiling method that identifies sites of DNA binding protein enrichment genome-wide with high signal to noise and low sequencing requirements. Currently, the analysis of CUT&RUN data is complicated by its exceptionally low background, which renders programs designed for analysis of ChIP-seq data vulnerable to oversensitivity in identifying sites of protein binding. RESULTS: Here we introduce Sparse Enrichment Analysis for CUT&RUN (SEACR), an analysis strategy that uses the global distribution of background signal to calibrate a simple threshold for peak calling. SEACR discriminates between true and false-positive peaks with near-perfect specificity from “gold standard” CUT&RUN datasets and efficiently identifies enriched regions for several different protein targets. We also introduce a web server (http://seacr.fredhutch.org) for plug-and-play analysis with SEACR that facilitates maximum accessibility across users of all skill levels. CONCLUSIONS: SEACR is a highly selective peak caller that definitively validates the accuracy of CUT&RUN for datasets with known true negatives. Its ease of use and performance in comparison with existing peak calling strategies make it an ideal choice for analyzing CUT&RUN data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13072-019-0287-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6624997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66249972019-07-23 Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling Meers, Michael P. Tenenbaum, Dan Henikoff, Steven Epigenetics Chromatin Methodology BACKGROUND: CUT&RUN is an efficient epigenome profiling method that identifies sites of DNA binding protein enrichment genome-wide with high signal to noise and low sequencing requirements. Currently, the analysis of CUT&RUN data is complicated by its exceptionally low background, which renders programs designed for analysis of ChIP-seq data vulnerable to oversensitivity in identifying sites of protein binding. RESULTS: Here we introduce Sparse Enrichment Analysis for CUT&RUN (SEACR), an analysis strategy that uses the global distribution of background signal to calibrate a simple threshold for peak calling. SEACR discriminates between true and false-positive peaks with near-perfect specificity from “gold standard” CUT&RUN datasets and efficiently identifies enriched regions for several different protein targets. We also introduce a web server (http://seacr.fredhutch.org) for plug-and-play analysis with SEACR that facilitates maximum accessibility across users of all skill levels. CONCLUSIONS: SEACR is a highly selective peak caller that definitively validates the accuracy of CUT&RUN for datasets with known true negatives. Its ease of use and performance in comparison with existing peak calling strategies make it an ideal choice for analyzing CUT&RUN data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13072-019-0287-4) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-12 /pmc/articles/PMC6624997/ /pubmed/31300027 http://dx.doi.org/10.1186/s13072-019-0287-4 Text en © The Author(s) 2019 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 | Methodology Meers, Michael P. Tenenbaum, Dan Henikoff, Steven Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling |
title | Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling |
title_full | Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling |
title_fullStr | Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling |
title_full_unstemmed | Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling |
title_short | Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling |
title_sort | peak calling by sparse enrichment analysis for cut&run chromatin profiling |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624997/ https://www.ncbi.nlm.nih.gov/pubmed/31300027 http://dx.doi.org/10.1186/s13072-019-0287-4 |
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