Comprehensive guide for epigenetics and transcriptomics data quality control
Summary: Host response to environmental exposures such as pathogens and chemicals can include modifications to the epigenome and transcriptome. Improved signature discovery, including the identification of the agent and timing of exposure, has been enabled by advancements in assaying techniques to d...
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| Language: | English |
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Elsevier
2025-03-01
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| Series: | STAR Protocols |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666166725000139 |
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| author | Arianna Comendul Frederique Ruf-Zamojski Colby T. Ford Pankaj Agarwal Elena Zaslavsky German Nudelman Manoj Hariharan Aliza Rubenstein Hanna Pincas Venugopalan D. Nair Adam M. Michaleas Philip D. Fremont-Smith Darrell O. Ricke Stuart C. Sealfon Christopher W. Woods Kajal T. Claypool Rafael Jaimes, III |
| author_facet | Arianna Comendul Frederique Ruf-Zamojski Colby T. Ford Pankaj Agarwal Elena Zaslavsky German Nudelman Manoj Hariharan Aliza Rubenstein Hanna Pincas Venugopalan D. Nair Adam M. Michaleas Philip D. Fremont-Smith Darrell O. Ricke Stuart C. Sealfon Christopher W. Woods Kajal T. Claypool Rafael Jaimes, III |
| author_sort | Arianna Comendul |
| collection | DOAJ |
| description | Summary: Host response to environmental exposures such as pathogens and chemicals can include modifications to the epigenome and transcriptome. Improved signature discovery, including the identification of the agent and timing of exposure, has been enabled by advancements in assaying techniques to detect RNA expression, DNA base modifications, histone modifications, and chromatin accessibility. The interrogation of the epigenome and transcriptome cascade requires analyzing disparate datasets from multiple assay types, often at single-cell resolution, derived from the same biospecimen. However, there remains a paucity of rigorous quality control standards of those datasets that reflect quality assurance of the underlying assay. This guide outlines a comprehensive suite of metrics that can be used to ensure quality from 11 different epigenetics and transcriptomics assays. Recommended mitigative actions to address failed metrics are provided. The workflow presented aims to improve benchwork protocols and dataset quality to enable accurate discovery of exposure signatures. |
| format | Article |
| id | doaj-art-92feeb48123649b39729fc936556a9d9 |
| institution | Kabale University |
| issn | 2666-1667 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | STAR Protocols |
| spelling | doaj-art-92feeb48123649b39729fc936556a9d92025-01-28T04:14:54ZengElsevierSTAR Protocols2666-16672025-03-0161103607Comprehensive guide for epigenetics and transcriptomics data quality controlArianna Comendul0Frederique Ruf-Zamojski1Colby T. Ford2Pankaj Agarwal3Elena Zaslavsky4German Nudelman5Manoj Hariharan6Aliza Rubenstein7Hanna Pincas8Venugopalan D. Nair9Adam M. Michaleas10Philip D. Fremont-Smith11Darrell O. Ricke12Stuart C. Sealfon13Christopher W. Woods14Kajal T. Claypool15Rafael Jaimes, III16Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USACedars-Sinai Medical Center, Department of Medicine, Los Angeles, CA, USA; Icahn School of Medicine at Mount Sinai, New York, NY, USATuple LLC, Charlotte, NC, USA; University of North Carolina at Charlotte, Department of Bioinformatics and Genomics, Charlotte, NC, USA; University of North Carolina at Charlotte, Center for Computational Intelligence to Predict Health and Environmental Risks (CIPHER), Charlotte, NC, USADuke University, Durham, NC, USAIcahn School of Medicine at Mount Sinai, New York, NY, USAIcahn School of Medicine at Mount Sinai, New York, NY, USAGenomic Analysis Laboratory, Salk Institute, La Jolla, CA, USAIcahn School of Medicine at Mount Sinai, New York, NY, USAIcahn School of Medicine at Mount Sinai, New York, NY, USAIcahn School of Medicine at Mount Sinai, New York, NY, USALincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USALincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USALincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USAIcahn School of Medicine at Mount Sinai, New York, NY, USADuke University, Durham, NC, USALincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USALincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA; Corresponding authorSummary: Host response to environmental exposures such as pathogens and chemicals can include modifications to the epigenome and transcriptome. Improved signature discovery, including the identification of the agent and timing of exposure, has been enabled by advancements in assaying techniques to detect RNA expression, DNA base modifications, histone modifications, and chromatin accessibility. The interrogation of the epigenome and transcriptome cascade requires analyzing disparate datasets from multiple assay types, often at single-cell resolution, derived from the same biospecimen. However, there remains a paucity of rigorous quality control standards of those datasets that reflect quality assurance of the underlying assay. This guide outlines a comprehensive suite of metrics that can be used to ensure quality from 11 different epigenetics and transcriptomics assays. Recommended mitigative actions to address failed metrics are provided. The workflow presented aims to improve benchwork protocols and dataset quality to enable accurate discovery of exposure signatures.http://www.sciencedirect.com/science/article/pii/S2666166725000139BioinformaticsSequence analysisRNAseq |
| spellingShingle | Arianna Comendul Frederique Ruf-Zamojski Colby T. Ford Pankaj Agarwal Elena Zaslavsky German Nudelman Manoj Hariharan Aliza Rubenstein Hanna Pincas Venugopalan D. Nair Adam M. Michaleas Philip D. Fremont-Smith Darrell O. Ricke Stuart C. Sealfon Christopher W. Woods Kajal T. Claypool Rafael Jaimes, III Comprehensive guide for epigenetics and transcriptomics data quality control STAR Protocols Bioinformatics Sequence analysis RNAseq |
| title | Comprehensive guide for epigenetics and transcriptomics data quality control |
| title_full | Comprehensive guide for epigenetics and transcriptomics data quality control |
| title_fullStr | Comprehensive guide for epigenetics and transcriptomics data quality control |
| title_full_unstemmed | Comprehensive guide for epigenetics and transcriptomics data quality control |
| title_short | Comprehensive guide for epigenetics and transcriptomics data quality control |
| title_sort | comprehensive guide for epigenetics and transcriptomics data quality control |
| topic | Bioinformatics Sequence analysis RNAseq |
| url | http://www.sciencedirect.com/science/article/pii/S2666166725000139 |
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