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Leveraging biological replicates to improve analysis in ChIP-seq experiments
ChIP-seq experiments identify genome-wide profiles of DNA-binding molecules including transcription factors, enzymes and epigenetic marks. Biological replicates are critical for reliable site discovery and are required for the deposition of data in the ENCODE and modENCODE projects. While early repo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Research Network of Computational and Structural Biotechnology (RNCSB) Organization
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3962196/ https://www.ncbi.nlm.nih.gov/pubmed/24688750 http://dx.doi.org/10.5936/csbj.201401002 |
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author | Yang, Yajie Fear, Justin Hu, Jianhong Haecker, Irina Zhou, Lei Renne, Rolf Bloom, David McIntyre, Lauren M |
author_facet | Yang, Yajie Fear, Justin Hu, Jianhong Haecker, Irina Zhou, Lei Renne, Rolf Bloom, David McIntyre, Lauren M |
author_sort | Yang, Yajie |
collection | PubMed |
description | ChIP-seq experiments identify genome-wide profiles of DNA-binding molecules including transcription factors, enzymes and epigenetic marks. Biological replicates are critical for reliable site discovery and are required for the deposition of data in the ENCODE and modENCODE projects. While early reports suggested two replicates were sufficient, the widespread application of the technique has led to emerging consensus that the technique is noisy and that increasing replication may be worthwhile. Additional biological replicates also allow for quantitative assessment of differences between conditions. To date it has remained controversial about how to confirm peak identification and to determine signal strength across biological replicates, particularly when the number of replicates is greater than two. Using objective metrics, we evaluate the consistency of biological replicates in ChIP-seq experiments with more than two replicates. We compare several approaches for binding site determination, including two popular but disparate peak callers, CisGenome and MACS2. Here we propose read coverage as a quantitative measurement of signal strength for estimating sample concordance. Determining binding based on genomic features, such as promoters, is also examined. We find that increasing the number of biological replicates increases the reliability of peak identification. Critically, binding sites with strong biological evidence may be missed if researchers rely on only two biological replicates. When more than two replicates are performed, a simple majority rule (>50% of samples identify a peak) identifies peaks more reliably in all biological replicates than the absolute concordance of peak identification between any two replicates, further demonstrating the utility of increasing replicate numbers in ChIP-seq experiments. |
format | Online Article Text |
id | pubmed-3962196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Research Network of Computational and Structural Biotechnology (RNCSB) Organization |
record_format | MEDLINE/PubMed |
spelling | pubmed-39621962014-03-31 Leveraging biological replicates to improve analysis in ChIP-seq experiments Yang, Yajie Fear, Justin Hu, Jianhong Haecker, Irina Zhou, Lei Renne, Rolf Bloom, David McIntyre, Lauren M Comput Struct Biotechnol J Research Article ChIP-seq experiments identify genome-wide profiles of DNA-binding molecules including transcription factors, enzymes and epigenetic marks. Biological replicates are critical for reliable site discovery and are required for the deposition of data in the ENCODE and modENCODE projects. While early reports suggested two replicates were sufficient, the widespread application of the technique has led to emerging consensus that the technique is noisy and that increasing replication may be worthwhile. Additional biological replicates also allow for quantitative assessment of differences between conditions. To date it has remained controversial about how to confirm peak identification and to determine signal strength across biological replicates, particularly when the number of replicates is greater than two. Using objective metrics, we evaluate the consistency of biological replicates in ChIP-seq experiments with more than two replicates. We compare several approaches for binding site determination, including two popular but disparate peak callers, CisGenome and MACS2. Here we propose read coverage as a quantitative measurement of signal strength for estimating sample concordance. Determining binding based on genomic features, such as promoters, is also examined. We find that increasing the number of biological replicates increases the reliability of peak identification. Critically, binding sites with strong biological evidence may be missed if researchers rely on only two biological replicates. When more than two replicates are performed, a simple majority rule (>50% of samples identify a peak) identifies peaks more reliably in all biological replicates than the absolute concordance of peak identification between any two replicates, further demonstrating the utility of increasing replicate numbers in ChIP-seq experiments. Research Network of Computational and Structural Biotechnology (RNCSB) Organization 2014-01-31 /pmc/articles/PMC3962196/ /pubmed/24688750 http://dx.doi.org/10.5936/csbj.201401002 Text en © Yang et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited. |
spellingShingle | Research Article Yang, Yajie Fear, Justin Hu, Jianhong Haecker, Irina Zhou, Lei Renne, Rolf Bloom, David McIntyre, Lauren M Leveraging biological replicates to improve analysis in ChIP-seq experiments |
title | Leveraging biological replicates to improve analysis in ChIP-seq experiments |
title_full | Leveraging biological replicates to improve analysis in ChIP-seq experiments |
title_fullStr | Leveraging biological replicates to improve analysis in ChIP-seq experiments |
title_full_unstemmed | Leveraging biological replicates to improve analysis in ChIP-seq experiments |
title_short | Leveraging biological replicates to improve analysis in ChIP-seq experiments |
title_sort | leveraging biological replicates to improve analysis in chip-seq experiments |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3962196/ https://www.ncbi.nlm.nih.gov/pubmed/24688750 http://dx.doi.org/10.5936/csbj.201401002 |
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