Comprehensive Guide of Epigenetics and Transcriptomics Data Quality Control Article Swipe
Arianna Comendul
,
Frederique Ruf-Zamojski
,
Colby T. Ford
,
Pankaj Agarwal
,
Elena Zaslavsky
,
German Nudelman
,
Manoj Hariharan
,
Aliza B. Rubenstein
,
Hanna Pinças
,
Venugopalan D. Nair
,
Adam Michaleas
,
Stuart C. Sealfon
,
Christopher W. Woods
,
Kajal Claypool
,
Rafael Jaimes
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.08.02.606411
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.08.02.606411
Host response to environmental exposures such as pathogens and chemicals can cause modifications to the epigenome and transcriptome. Analysis of these modifications can reveal signatures with regards to the agent and timing of exposure. Exhaustive interrogation of the cascade of the epigenome and transcriptome requires analysis of disparate datasets from multiple assay types, often at single cell resolution, from the same biospecimen. Improved signature discovery has been enabled by advancements in assaying techniques to detect RNA expression, DNA base modifications, histone modifications, and chromatin accessibility. 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. Recommendations on mitigation approaches to address failed metrics and poor quality data are provided. The workflow consists of assessing dataset quality and reiterating benchwork protocols for improved results to generate accurate exposure signatures.
Related Topics
Concepts
Epigenome
Workflow
Computational biology
Computer science
Quality (philosophy)
Epigenetics
Epigenomics
Transcriptome
Histone
Chromatin
Data mining
Data science
Biology
DNA methylation
Genetics
Gene expression
DNA
Gene
Database
Epistemology
Philosophy
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2024.08.02.606411
- https://www.biorxiv.org/content/biorxiv/early/2024/08/06/2024.08.02.606411.full.pdf
- OA Status
- green
- References
- 71
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401406573
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4401406573Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2024.08.02.606411Digital Object Identifier
- Title
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Comprehensive Guide of Epigenetics and Transcriptomics Data Quality ControlWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-08-06Full publication date if available
- Authors
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Arianna Comendul, Frederique Ruf-Zamojski, Colby T. Ford, Pankaj Agarwal, Elena Zaslavsky, German Nudelman, Manoj Hariharan, Aliza B. Rubenstein, Hanna Pinças, Venugopalan D. Nair, Adam Michaleas, Stuart C. Sealfon, Christopher W. Woods, Kajal Claypool, Rafael JaimesList of authors in order
- Landing page
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https://doi.org/10.1101/2024.08.02.606411Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2024/08/06/2024.08.02.606411.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2024/08/06/2024.08.02.606411.full.pdfDirect OA link when available
- Concepts
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Epigenome, Workflow, Computational biology, Computer science, Quality (philosophy), Epigenetics, Epigenomics, Transcriptome, Histone, Chromatin, Data mining, Data science, Biology, DNA methylation, Genetics, Gene expression, DNA, Gene, Database, Epistemology, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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71Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.exposures | 4 |
| abstract_inverted_index.pathogens | 7 |
| abstract_inverted_index.protocols | 152 |
| abstract_inverted_index.provided. | 141 |
| abstract_inverted_index.signature | 63 |
| abstract_inverted_index.standards | 94 |
| abstract_inverted_index.Exhaustive | 34 |
| abstract_inverted_index.approaches | 131 |
| abstract_inverted_index.mitigation | 130 |
| abstract_inverted_index.signatures | 24 |
| abstract_inverted_index.techniques | 72 |
| abstract_inverted_index.underlying | 104 |
| abstract_inverted_index.epigenetics | 124 |
| abstract_inverted_index.expression, | 76 |
| abstract_inverted_index.reiterating | 150 |
| abstract_inverted_index.resolution, | 57 |
| abstract_inverted_index.signatures. | 160 |
| abstract_inverted_index.advancements | 69 |
| abstract_inverted_index.biospecimen. | 61 |
| abstract_inverted_index.comprehensive | 110 |
| abstract_inverted_index.environmental | 3 |
| abstract_inverted_index.interrogation | 35 |
| abstract_inverted_index.modifications | 12, 21 |
| abstract_inverted_index.transcriptome | 43 |
| abstract_inverted_index.accessibility. | 84 |
| abstract_inverted_index.modifications, | 79, 81 |
| abstract_inverted_index.transcriptome. | 17 |
| abstract_inverted_index.Recommendations | 128 |
| abstract_inverted_index.transcriptomics | 126 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5007734013 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 15 |
| corresponding_institution_ids | https://openalex.org/I4210122954, https://openalex.org/I63966007 |
| citation_normalized_percentile.value | 0.14188399 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |