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bioRxiv · 10.1101/2023.10.11.561933

Regulatory Landscape Enrichment Analysis (RLEA) using gaiaAssociation

Sosa, E. A.·Rosean, S.·O'Shea, D.·Raj, S. M.·Seoighe, C.·Greally, J. M.
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Abstract

MotivationTo understand whether sets of genomic loci are enriched at the regulatory loci of one or more cell types, we developed the gaiaAssociation package to perform Regulatory Landscape Enrichment Analysis (RLEA). RLEA is a novel analytical process that tests for enrichment of sets of loci in cell type-specific open chromatin regions (OCRs) in the genome. ResultsWe demonstrate that the application of RLEA to genome-wide association study (GWAS) data reveals cell types likely to be mediating the phenotype studied, and clusters OCRs based on their shared regulatory profiles. GaiaAssociation is Python code that is freely available for use in functional genomics studies. Availability and ImplementationGaia Association is available on PyPi (https://pypi.org/project/gaiaAssociation/0.6.0/#description) for pip download and use on the command line or as an inline Python package. Gaia Association can also be installed from GitHub at https://github.com/GreallyLab/gaiaAssociation. Contactjohn.greally@einsteinmed.edu

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Sosa, E. A., Rosean, S., O'Shea, D., Raj, S. M., Seoighe, C., Greally, J. M.. 2023-10-16. Regulatory Landscape Enrichment Analysis (RLEA) using gaiaAssociation. https://doi.org/10.1101/2023.10.11.561933

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