PascalX: a Python library for GWAS gene and pathway enrichment tests.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 37137228.
- Also identified by DOI 10.1093/bioinformatics/btad296 and PMC identifier 10185402.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
'PascalX' is a Python library providing fast and accurate tools for mapping SNP-wise GWAS summary statistics. Specifically, it allows for scoring genes and annotated gene sets for enrichment signals based on data from, both, single GWAS and pairs of GWAS. The gene scores take into account the correlation pattern between SNPs. They are based on the cumulative density function of a linear combination of χ2 distributed random variables, which can be calculated either approximately or exactly to high precision. Acceleration via multithreading and GPU is supported. The code of PascalX is fully open source and well suited as a base for method development in the GWAS enrichment test context. The source code is available at https://github.com/BergmannLab/PascalX and archived under doi://10.5281/zenodo.4429922. A user manual with usage examples is available at https://bergmannlab.github.io/PascalX/.
Medical subject headings
- Genome-Wide Association Study
- Libraries