LDGMs (Linkage Disequilibrium Graphical Models) are sparse and accurate models of linkage disequilibrium (LD) which massively accelerate matrix algebra computations in statistical genetics.
Please refer to the documentation for information on installing and using the software.
Please cite this paper if you use LDGMs in published work.
Pouria Salehi Nowbandegani, Anthony Wilder Wohns, Jenna L. Ballard, Eric S. Lander, Alex Bloemendal, Benjamin M. Neale, and Luke J. O’Connor (2023) Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies. Nat Genet. DOI: 10.1038/s41588-023-01487-8
- Python API and CLI for applications including polygenic scores and heritability partitioning: https://github.com/oclb/graphld
- LDGM-VCF specification and bcftools plugin for computing polygenic scores with LDGMs: https://github.com/freeseek/score
- For linear algebra with sparse matrices, SuiteSparse: https://github.com/DrTimothyAldenDavis/SuiteSparse
