CWAS-Plus: estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data Article Swipe
Yujin Kim
,
Minwoo Jeong
,
In Gyeong Koh
,
Chanhee Kim
,
Hyeji Lee
,
Jae Hyun Kim
,
Ronald Yurko
,
Il Bin Kim
,
Jeongbin Park
,
Donna M. Werling
,
Stephan Sanders
,
Joon‐Yong An
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/bib/bbae323
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/bib/bbae323
Variants in cis-regulatory elements link the noncoding genome to human pathology; however, detailed analytic tools for understanding the association between cell-level brain pathology and noncoding variants are lacking. CWAS-Plus, adapted from a Python package for category-wide association testing (CWAS), enhances noncoding variant analysis by integrating both whole-genome sequencing (WGS) and user-provided functional data. With simplified parameter settings and an efficient multiple testing correction method, CWAS-Plus conducts the CWAS workflow 50 times faster than CWAS, making it more accessible and user-friendly for researchers. Here, we used a single-nuclei assay for transposase-accessible chromatin with sequencing to facilitate CWAS-guided noncoding variant analysis at cell-type-specific enhancers and promoters. Examining autism spectrum disorder WGS data (n = 7280), CWAS-Plus identified noncoding de novo variant associations in transcription factor binding sites within conserved loci. Independently, in Alzheimer’s disease WGS data (n = 1087), CWAS-Plus detected rare noncoding variant associations in microglia-specific regulatory elements. These findings highlight CWAS-Plus’s utility in genomic disorders and scalability for processing large-scale WGS data and in multiple-testing corrections. CWAS-Plus and its user manual are available at https://github.com/joonan-lab/cwas/ and https://cwas-plus.readthedocs.io/en/latest/, respectively.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/bib/bbae323
- https://academic.oup.com/bib/article-pdf/25/4/bbae323/58447340/bbae323.pdf
- OA Status
- gold
- Cited By
- 11
- References
- 63
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4400378164
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4400378164Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/bib/bbae323Digital Object Identifier
- Title
-
CWAS-Plus: estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional dataWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-05-23Full publication date if available
- Authors
-
Yujin Kim, Minwoo Jeong, In Gyeong Koh, Chanhee Kim, Hyeji Lee, Jae Hyun Kim, Ronald Yurko, Il Bin Kim, Jeongbin Park, Donna M. Werling, Stephan Sanders, Joon‐Yong AnList of authors in order
- Landing page
-
https://doi.org/10.1093/bib/bbae323Publisher landing page
- PDF URL
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https://academic.oup.com/bib/article-pdf/25/4/bbae323/58447340/bbae323.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://academic.oup.com/bib/article-pdf/25/4/bbae323/58447340/bbae323.pdfDirect OA link when available
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Computational biology, Biology, Epigenomics, Genetics, DNA methylation, Gene, Gene expressionTop concepts (fields/topics) attached by OpenAlex
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11Total citation count in OpenAlex
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2025: 9, 2024: 2Per-year citation counts (last 5 years)
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63Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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