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SEAseq: a portable and cloud-based chromatin occupancy analysis suite
BACKGROUND: Genome-wide protein-DNA binding is popularly assessed using specific antibody pulldown in Chromatin Immunoprecipitation Sequencing (ChIP-Seq) or Cleavage Under Targets and Release Using Nuclease (CUT&RUN) sequencing experiments. These technologies generate high-throughput sequencing...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864840/ https://www.ncbi.nlm.nih.gov/pubmed/35193506 http://dx.doi.org/10.1186/s12859-022-04588-z |
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author | O. Adetunji, Modupeore J. Abraham, Brian |
author_facet | O. Adetunji, Modupeore J. Abraham, Brian |
author_sort | O. Adetunji, Modupeore |
collection | PubMed |
description | BACKGROUND: Genome-wide protein-DNA binding is popularly assessed using specific antibody pulldown in Chromatin Immunoprecipitation Sequencing (ChIP-Seq) or Cleavage Under Targets and Release Using Nuclease (CUT&RUN) sequencing experiments. These technologies generate high-throughput sequencing data that necessitate the use of multiple sophisticated, computationally intensive genomic tools to make discoveries, but these genomic tools often have a high barrier to use because of computational resource constraints. RESULTS: We present a comprehensive, infrastructure-independent, computational pipeline called SEAseq, which leverages field-standard, open-source tools for processing and analyzing ChIP-Seq/CUT&RUN data. SEAseq performs extensive analyses from the raw output of the experiment, including alignment, peak calling, motif analysis, promoters and metagene coverage profiling, peak annotation distribution, clustered/stitched peaks (e.g. super-enhancer) identification, and multiple relevant quality assessment metrics, as well as automatic interfacing with data in GEO/SRA. SEAseq enables rapid and cost-effective resource for analysis of both new and publicly available datasets as demonstrated in our comparative case studies. CONCLUSIONS: The easy-to-use and versatile design of SEAseq makes it a reliable and efficient resource for ensuring high quality analysis. Its cloud implementation enables a broad suite of analyses in environments with constrained computational resources. SEAseq is platform-independent and is aimed to be usable by everyone with or without programming skills. It is available on the cloud at https://platform.stjude.cloud/workflows/seaseq and can be locally installed from the repository at https://github.com/stjude/seaseq. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04588-z. |
format | Online Article Text |
id | pubmed-8864840 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88648402022-02-23 SEAseq: a portable and cloud-based chromatin occupancy analysis suite O. Adetunji, Modupeore J. Abraham, Brian BMC Bioinformatics Software BACKGROUND: Genome-wide protein-DNA binding is popularly assessed using specific antibody pulldown in Chromatin Immunoprecipitation Sequencing (ChIP-Seq) or Cleavage Under Targets and Release Using Nuclease (CUT&RUN) sequencing experiments. These technologies generate high-throughput sequencing data that necessitate the use of multiple sophisticated, computationally intensive genomic tools to make discoveries, but these genomic tools often have a high barrier to use because of computational resource constraints. RESULTS: We present a comprehensive, infrastructure-independent, computational pipeline called SEAseq, which leverages field-standard, open-source tools for processing and analyzing ChIP-Seq/CUT&RUN data. SEAseq performs extensive analyses from the raw output of the experiment, including alignment, peak calling, motif analysis, promoters and metagene coverage profiling, peak annotation distribution, clustered/stitched peaks (e.g. super-enhancer) identification, and multiple relevant quality assessment metrics, as well as automatic interfacing with data in GEO/SRA. SEAseq enables rapid and cost-effective resource for analysis of both new and publicly available datasets as demonstrated in our comparative case studies. CONCLUSIONS: The easy-to-use and versatile design of SEAseq makes it a reliable and efficient resource for ensuring high quality analysis. Its cloud implementation enables a broad suite of analyses in environments with constrained computational resources. SEAseq is platform-independent and is aimed to be usable by everyone with or without programming skills. It is available on the cloud at https://platform.stjude.cloud/workflows/seaseq and can be locally installed from the repository at https://github.com/stjude/seaseq. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04588-z. BioMed Central 2022-02-23 /pmc/articles/PMC8864840/ /pubmed/35193506 http://dx.doi.org/10.1186/s12859-022-04588-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 | Software O. Adetunji, Modupeore J. Abraham, Brian SEAseq: a portable and cloud-based chromatin occupancy analysis suite |
title | SEAseq: a portable and cloud-based chromatin occupancy analysis suite |
title_full | SEAseq: a portable and cloud-based chromatin occupancy analysis suite |
title_fullStr | SEAseq: a portable and cloud-based chromatin occupancy analysis suite |
title_full_unstemmed | SEAseq: a portable and cloud-based chromatin occupancy analysis suite |
title_short | SEAseq: a portable and cloud-based chromatin occupancy analysis suite |
title_sort | seaseq: a portable and cloud-based chromatin occupancy analysis suite |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864840/ https://www.ncbi.nlm.nih.gov/pubmed/35193506 http://dx.doi.org/10.1186/s12859-022-04588-z |
work_keys_str_mv | AT oadetunjimodupeore seaseqaportableandcloudbasedchromatinoccupancyanalysissuite AT jabrahambrian seaseqaportableandcloudbasedchromatinoccupancyanalysissuite |