Cargando…

Analyzing histone ChIP-seq data with a bin-based probability of being signal

Histone ChIP-seq is one of the primary methods for charting the cellular epigenomic landscape, the components of which play a critical regulatory role in gene expression. Analyzing the activity of regulatory elements across datasets and cell types can be challenging due to shifting peak positions an...

Descripción completa

Detalles Bibliográficos
Autores principales: Hecht, Vivian, Dong, Kevin, Rajesh, Sreshtaa, Shpilker, Polina, Wekhande, Siddarth, Shoresh, Noam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10619820/
https://www.ncbi.nlm.nih.gov/pubmed/37862349
http://dx.doi.org/10.1371/journal.pcbi.1011568
_version_ 1785130072304254976
author Hecht, Vivian
Dong, Kevin
Rajesh, Sreshtaa
Shpilker, Polina
Wekhande, Siddarth
Shoresh, Noam
author_facet Hecht, Vivian
Dong, Kevin
Rajesh, Sreshtaa
Shpilker, Polina
Wekhande, Siddarth
Shoresh, Noam
author_sort Hecht, Vivian
collection PubMed
description Histone ChIP-seq is one of the primary methods for charting the cellular epigenomic landscape, the components of which play a critical regulatory role in gene expression. Analyzing the activity of regulatory elements across datasets and cell types can be challenging due to shifting peak positions and normalization artifacts resulting from, for example, differing read depths, ChIP efficiencies, and target sizes. Moreover, broad regions of enrichment seen in repressive histone marks often evade detection by commonly used peak callers. Here, we present a simple and versatile method for identifying enriched regions in ChIP-seq data that relies on estimating a gamma distribution fit to non-overlapping 5kB genomic bins to establish a global background. We use this distribution to assign a probability of being signal (PBS) between zero and one to each 5 kB bin. This approach, while lower in resolution than typical peak-calling methods, provides a straightforward way to identify enriched regions and compare enrichments among multiple datasets, by transforming the data to values that are universally normalized and can be readily visualized and integrated with downstream analysis methods. We demonstrate applications of PBS for both broad and narrow histone marks, and provide several illustrations of biological insights which can be gleaned by integrating PBS scores with downstream data types.
format Online
Article
Text
id pubmed-10619820
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-106198202023-11-02 Analyzing histone ChIP-seq data with a bin-based probability of being signal Hecht, Vivian Dong, Kevin Rajesh, Sreshtaa Shpilker, Polina Wekhande, Siddarth Shoresh, Noam PLoS Comput Biol Research Article Histone ChIP-seq is one of the primary methods for charting the cellular epigenomic landscape, the components of which play a critical regulatory role in gene expression. Analyzing the activity of regulatory elements across datasets and cell types can be challenging due to shifting peak positions and normalization artifacts resulting from, for example, differing read depths, ChIP efficiencies, and target sizes. Moreover, broad regions of enrichment seen in repressive histone marks often evade detection by commonly used peak callers. Here, we present a simple and versatile method for identifying enriched regions in ChIP-seq data that relies on estimating a gamma distribution fit to non-overlapping 5kB genomic bins to establish a global background. We use this distribution to assign a probability of being signal (PBS) between zero and one to each 5 kB bin. This approach, while lower in resolution than typical peak-calling methods, provides a straightforward way to identify enriched regions and compare enrichments among multiple datasets, by transforming the data to values that are universally normalized and can be readily visualized and integrated with downstream analysis methods. We demonstrate applications of PBS for both broad and narrow histone marks, and provide several illustrations of biological insights which can be gleaned by integrating PBS scores with downstream data types. Public Library of Science 2023-10-20 /pmc/articles/PMC10619820/ /pubmed/37862349 http://dx.doi.org/10.1371/journal.pcbi.1011568 Text en © 2023 Hecht et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hecht, Vivian
Dong, Kevin
Rajesh, Sreshtaa
Shpilker, Polina
Wekhande, Siddarth
Shoresh, Noam
Analyzing histone ChIP-seq data with a bin-based probability of being signal
title Analyzing histone ChIP-seq data with a bin-based probability of being signal
title_full Analyzing histone ChIP-seq data with a bin-based probability of being signal
title_fullStr Analyzing histone ChIP-seq data with a bin-based probability of being signal
title_full_unstemmed Analyzing histone ChIP-seq data with a bin-based probability of being signal
title_short Analyzing histone ChIP-seq data with a bin-based probability of being signal
title_sort analyzing histone chip-seq data with a bin-based probability of being signal
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10619820/
https://www.ncbi.nlm.nih.gov/pubmed/37862349
http://dx.doi.org/10.1371/journal.pcbi.1011568
work_keys_str_mv AT hechtvivian analyzinghistonechipseqdatawithabinbasedprobabilityofbeingsignal
AT dongkevin analyzinghistonechipseqdatawithabinbasedprobabilityofbeingsignal
AT rajeshsreshtaa analyzinghistonechipseqdatawithabinbasedprobabilityofbeingsignal
AT shpilkerpolina analyzinghistonechipseqdatawithabinbasedprobabilityofbeingsignal
AT wekhandesiddarth analyzinghistonechipseqdatawithabinbasedprobabilityofbeingsignal
AT shoreshnoam analyzinghistonechipseqdatawithabinbasedprobabilityofbeingsignal