.. PascalX documentation master file, created by sphinx-quickstart on Wed Nov 18 11:20:06 2020. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Welcome to PascalX's documentation! =================================== PascalX is a python3 library (`source `_) for high precision gene and pathway scoring for GWAS summary statistics. Aggregation of SNP p-values to gene and pathway scores follows the `Pascal `_ methodology, which is based on :math:`\chi^2` statistics. The cumulative distribution function of the weighted :math:`\chi^2` distribution can be calculated approximately or exactly via a multi-precision C++ implementation of Ruben's and Davies algorithm. This allows to apply the Pascal methodology to modern UK BioBank scale GWAS. In addition, PascalX offers a novel coherence test between two different GWAS on the level of genes, based on the product-normal distribution, as described `here `_. **Highlights:** * Multi-precision weighted :math:`\chi^2` cdf calculation (approximately or exactly up to 100 digits) * Parallelization over chromosomes and/or genes * GPU support for acceleration of linear algebra operations * Fast random access to reference panel genomic data via own indexed SNP database * Gene-wise coherence test between two GWAS * Support for SNP selection via external data * Tissue enrichment test (experimental) .. warning:: PascalX is a research level tool. No warranty or guarantee whatsoever for its correct functionality is given. You should perform your own consistency checks on results PascalX implies. .. toctree:: :maxdepth: 3 :caption: Contents install usage PascalX .. Index ================== * :ref:`genindex` License and citation policy --------------------------- The PascalX package is an open-source package under AGPLv3. If you make use of PascalX for your research, please cite the PascalX publication: | *Krefl D., Brandulas Cammarata A., Bergmann S.* | *PascalX: a python library for GWAS gene and pathway enrichment tests* | *Bioinformatics, btad296* | *doi:10.1093/bioinformatics/btad296* If you make use of the X-scorer (gene-wise coherence test between GWAS), please cite the work: | *Krefl D., Bergmann S.* | *Cross-GWAS coherence test at the gene and pathway level* | *PLOS Computational Biology 18(9): e1010517* | *doi:10.1371/journal.pcbi.1010517* Contact ------- * For all technical issues (bug reports, etc.), please open a ticket on the `GitHub `_ page.