PAPET: a collection of performant algorithms to identify 5-methyl cytosine from PacBio SequelII data Article Swipe
Romain Groux
,
Ioannis Xénarios
,
Emanuel Schmid‐Siegert
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.03.17.533149
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.03.17.533149
Background Cytosine followed by guanine (CpG) rich genomic regions are known important regulatory sequences among vertebrates. Their cytosines can be subjected to a variety of chemical modifications, one of which being 5-methylcytosine (5mC), usually coined CpG methylation. CpG methylation has been demonstrated to have a deep impact on the nearby regulated genes. The advent of single molecule real time sequencing methods have proven to be powerful enablers in this field of research because of the possibility to detect DNA chemical modification directly from the raw sequencing data. In this perspective, several 5mC detection methods have been proposed. Results In this work we present PAPET - PacBio Prediction of Epigenetic Toolkit - a computational method to detect 5mC directly from PacBio SequelII raw sequencing data. We characterized the 5mC signatures in the raw data and proposed a framework to model them. We also assessed the effect of the DNA sequence alone on the signal and propose a normalization method to leverage this effect. From this, we designed a probabilistic approach to predict the presence of cytosine methylation from the sequencing kinetics and benchmarked it. Conclusions We apply this framework to predict CpG methylation from SequelII data and demonstrate that the classifiers compare equally with PacBio’s prediction method counterparts in terms of AUC and achieve very high specificity and precision.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.03.17.533149
- https://www.biorxiv.org/content/biorxiv/early/2023/03/21/2023.03.17.533149.full.pdf
- OA Status
- green
- Cited By
- 1
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4328054978
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- OpenAlex ID
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https://openalex.org/W4328054978Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2023.03.17.533149Digital Object Identifier
- Title
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PAPET: a collection of performant algorithms to identify 5-methyl cytosine from PacBio SequelII dataWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
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2023-03-21Full publication date if available
- Authors
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Romain Groux, Ioannis Xénarios, Emanuel Schmid‐SiegertList of authors in order
- Landing page
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https://doi.org/10.1101/2023.03.17.533149Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2023/03/21/2023.03.17.533149.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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-
greenOpen access status per OpenAlex
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https://www.biorxiv.org/content/biorxiv/early/2023/03/21/2023.03.17.533149.full.pdfDirect OA link when available
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Computer science, Scalability, Set (abstract data type), Source code, Pace, DNA methylation, Class (philosophy), Data mining, Machine learning, Artificial intelligence, Gene, Biology, Database, Programming language, Genetics, Geography, Geodesy, Gene expressionTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2024: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.(5mC), | 33 |
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| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5061688204 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/8 |
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| sustainable_development_goals[0].display_name | Decent work and economic growth |
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