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Rescuing biologically relevant consensus regions across replicated samples
BACKGROUND: Protein-DNA binding sites of ChIP-seq experiments are identified where the binding affinity is significant based on a given threshold. The choice of the threshold is a trade-off between conservative region identification and discarding weak, but true binding sites. RESULTS: We rescue wea...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246347/ https://www.ncbi.nlm.nih.gov/pubmed/37286963 http://dx.doi.org/10.1186/s12859-023-05340-x |
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author | Jalili, Vahid Cremona, Marzia A. Palluzzi, Fernando |
author_facet | Jalili, Vahid Cremona, Marzia A. Palluzzi, Fernando |
author_sort | Jalili, Vahid |
collection | PubMed |
description | BACKGROUND: Protein-DNA binding sites of ChIP-seq experiments are identified where the binding affinity is significant based on a given threshold. The choice of the threshold is a trade-off between conservative region identification and discarding weak, but true binding sites. RESULTS: We rescue weak binding sites using MSPC, which efficiently exploits replicates to lower the threshold required to identify a site while keeping a low false-positive rate, and we compare it to IDR, a widely used post-processing method for identifying highly reproducible peaks across replicates. We observe several master transcription regulators (e.g., SP1 and GATA3) and HDAC2-GATA1 regulatory networks on rescued regions in K562 cell line. CONCLUSIONS: We argue the biological relevance of weak binding sites and the information they add when rescued by MSPC. An implementation of the proposed extended MSPC methodology and the scripts to reproduce the performed analysis are freely available at https://genometric.github.io/MSPC/; MSPC is distributed as a command-line application and an R package available from Bioconductor (https://doi.org/doi:10.18129/B9.bioc.rmspc). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05340-x. |
format | Online Article Text |
id | pubmed-10246347 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102463472023-06-08 Rescuing biologically relevant consensus regions across replicated samples Jalili, Vahid Cremona, Marzia A. Palluzzi, Fernando BMC Bioinformatics Research BACKGROUND: Protein-DNA binding sites of ChIP-seq experiments are identified where the binding affinity is significant based on a given threshold. The choice of the threshold is a trade-off between conservative region identification and discarding weak, but true binding sites. RESULTS: We rescue weak binding sites using MSPC, which efficiently exploits replicates to lower the threshold required to identify a site while keeping a low false-positive rate, and we compare it to IDR, a widely used post-processing method for identifying highly reproducible peaks across replicates. We observe several master transcription regulators (e.g., SP1 and GATA3) and HDAC2-GATA1 regulatory networks on rescued regions in K562 cell line. CONCLUSIONS: We argue the biological relevance of weak binding sites and the information they add when rescued by MSPC. An implementation of the proposed extended MSPC methodology and the scripts to reproduce the performed analysis are freely available at https://genometric.github.io/MSPC/; MSPC is distributed as a command-line application and an R package available from Bioconductor (https://doi.org/doi:10.18129/B9.bioc.rmspc). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05340-x. BioMed Central 2023-06-07 /pmc/articles/PMC10246347/ /pubmed/37286963 http://dx.doi.org/10.1186/s12859-023-05340-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Jalili, Vahid Cremona, Marzia A. Palluzzi, Fernando Rescuing biologically relevant consensus regions across replicated samples |
title | Rescuing biologically relevant consensus regions across replicated samples |
title_full | Rescuing biologically relevant consensus regions across replicated samples |
title_fullStr | Rescuing biologically relevant consensus regions across replicated samples |
title_full_unstemmed | Rescuing biologically relevant consensus regions across replicated samples |
title_short | Rescuing biologically relevant consensus regions across replicated samples |
title_sort | rescuing biologically relevant consensus regions across replicated samples |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246347/ https://www.ncbi.nlm.nih.gov/pubmed/37286963 http://dx.doi.org/10.1186/s12859-023-05340-x |
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