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Comparative analysis of commonly used peak calling programs for ChIP-Seq analysis

Chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-Seq) is a powerful technology to profile the location of proteins of interest on a whole-genome scale. To identify the enrichment location of proteins, many programs and algorithms have been proposed. However, none of th...

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Autores principales: Jeon, Hyeongrin, Lee, Hyunji, Kang, Byunghee, Jang, Insoon, Roh, Tae-Young
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808876/
https://www.ncbi.nlm.nih.gov/pubmed/33412758
http://dx.doi.org/10.5808/GI.2020.18.4.e42
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author Jeon, Hyeongrin
Lee, Hyunji
Kang, Byunghee
Jang, Insoon
Roh, Tae-Young
author_facet Jeon, Hyeongrin
Lee, Hyunji
Kang, Byunghee
Jang, Insoon
Roh, Tae-Young
author_sort Jeon, Hyeongrin
collection PubMed
description Chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-Seq) is a powerful technology to profile the location of proteins of interest on a whole-genome scale. To identify the enrichment location of proteins, many programs and algorithms have been proposed. However, none of the commonly used peak calling programs could accurately explain the binding features of target proteins detected by ChIP-Seq. Here, publicly available data on 12 histone modifications, including H3K4ac/me1/me2/me3, H3K9ac/me3, H3K27ac/me3, H3K36me3, H3K56ac, and H3K79me1/me2, generated from a human embryonic stem cell line (H1), were profiled with five peak callers (CisGenome, MACS1, MACS2, PeakSeq, and SISSRs). The performance of the peak calling programs was compared in terms of reproducibility between replicates, examination of enriched regions to variable sequencing depths, the specificity-to-noise signal, and sensitivity of peak prediction. There were no major differences among peak callers when analyzing point source histone modifications. The peak calling results from histone modifications with low fidelity, such as H3K4ac, H3K56ac, and H3K79me1/me2, showed low performance in all parameters, which indicates that their peak positions might not be located accurately. Our comparative results could provide a helpful guide to choose a suitable peak calling program for specific histone modifications.
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spelling pubmed-78088762021-01-26 Comparative analysis of commonly used peak calling programs for ChIP-Seq analysis Jeon, Hyeongrin Lee, Hyunji Kang, Byunghee Jang, Insoon Roh, Tae-Young Genomics Inform Original Article Chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-Seq) is a powerful technology to profile the location of proteins of interest on a whole-genome scale. To identify the enrichment location of proteins, many programs and algorithms have been proposed. However, none of the commonly used peak calling programs could accurately explain the binding features of target proteins detected by ChIP-Seq. Here, publicly available data on 12 histone modifications, including H3K4ac/me1/me2/me3, H3K9ac/me3, H3K27ac/me3, H3K36me3, H3K56ac, and H3K79me1/me2, generated from a human embryonic stem cell line (H1), were profiled with five peak callers (CisGenome, MACS1, MACS2, PeakSeq, and SISSRs). The performance of the peak calling programs was compared in terms of reproducibility between replicates, examination of enriched regions to variable sequencing depths, the specificity-to-noise signal, and sensitivity of peak prediction. There were no major differences among peak callers when analyzing point source histone modifications. The peak calling results from histone modifications with low fidelity, such as H3K4ac, H3K56ac, and H3K79me1/me2, showed low performance in all parameters, which indicates that their peak positions might not be located accurately. Our comparative results could provide a helpful guide to choose a suitable peak calling program for specific histone modifications. Korea Genome Organization 2020-12-14 /pmc/articles/PMC7808876/ /pubmed/33412758 http://dx.doi.org/10.5808/GI.2020.18.4.e42 Text en (c) 2020, Korea Genome Organization (CC) 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 work is properly cited.
spellingShingle Original Article
Jeon, Hyeongrin
Lee, Hyunji
Kang, Byunghee
Jang, Insoon
Roh, Tae-Young
Comparative analysis of commonly used peak calling programs for ChIP-Seq analysis
title Comparative analysis of commonly used peak calling programs for ChIP-Seq analysis
title_full Comparative analysis of commonly used peak calling programs for ChIP-Seq analysis
title_fullStr Comparative analysis of commonly used peak calling programs for ChIP-Seq analysis
title_full_unstemmed Comparative analysis of commonly used peak calling programs for ChIP-Seq analysis
title_short Comparative analysis of commonly used peak calling programs for ChIP-Seq analysis
title_sort comparative analysis of commonly used peak calling programs for chip-seq analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808876/
https://www.ncbi.nlm.nih.gov/pubmed/33412758
http://dx.doi.org/10.5808/GI.2020.18.4.e42
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