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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...

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Autores principales: Meers, Michael P., Tenenbaum, Dan, Henikoff, Steven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
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.
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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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