CWAS-Plus: Estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data
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Variants in cis-regulatory elements link the noncoding genome to human brain 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) employs both whole-genome sequencing and user-provided functional data to enhance noncoding variant analysis, with a faster and more efficient execution of the CWAS workflow. Here, we used 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 whole-genome sequencing data (n = 7,280), CWAS-Plus identified noncoding de novo variant associations in transcription factor binding sites within conserved loci. Independently, in Alzheimer’s disease whole-genome sequencing data (n = 1,087), 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 whole-genome sequencing 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.
KEY POINTS
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CWAS-Plus efficiently identifies noncoding associations in WGS data, supporting user-friendly categorization and burden enrichment tests.
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CWAS-Plus integrates various functional datasets, emphasizing cell-type-specific noncoding associations.
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CWAS-Plus provides a novel approach for multiple testing correction, enhancing the reliability of the results.
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Autism spectrum disorder risk noncoding variants are identified as enriched with transcription factors, suggesting their role in the pathology.
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Rare variant analysis with Alzheimer’s disease samples reveals strong association with microglia, supporting the reliability of the results produced by CWAS-Plus.