ArticleBioinformatics (Oxford, England)2023
PascalX: a Python library for GWAS gene and pathway enrichment tests.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 22 citations in OpenAlex.
- Deep learning aging marker from retinal images unveils sex-specific clinical and genetic signatures.Nature communications · 2026Article
- Integration of genetic evidence to identify approved drug targets.Genome medicine · 2026Article
- Bidirectional genetic and phenotypic links between smoking and striatal iron content involving dopaminergic and inflammatory pathways.Addiction (Abingdon, England) · 2026Article
- Histone H1 variants regulate neurodevelopmental transcriptional programs in autism with 16p11.2 deletion.Genome biology · 2026Article
- Cross-organ analysis reveals associations between vascular properties of the retina, the carotid and aortic arteries, and the brain.Communications medicine · 2026Article
- Identification of rare disease genes as drivers of common diseases through tissue-specific gene regulatory networks.Scientific reports · 2024Article
- Phenotypic and genetic characteristics of retinal vascular parameters and their association with diseases.Nature communications · 2024Article
- The goldmine of GWAS summary statistics: a systematic review of methods and tools.BioData mining · 2024Article
- Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes.BMC medical genomics · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
summary'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. AVAILABILITY AND IMPLEMENTATION: 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/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.