SNPknock is a simple Python package for creating knockoffs of hidden Markov models and genetic data.
This package implements the algorithms described in the following papers:
- "Gene hunting with hidden Markov model knockoffs", Sesia et al., Biometrika, 2019, https://dx.doi.org/10.1093/biomet/asy033
- "Multi-resolution localization of causal variants across the genome", Sesia et al., bioRxiv, 2019, https://dx.doi.org/10.1101/631390
Feature highlights:
- Generate knockoffs for discrete Markov chains (DMC).
- Generate knockoffs for hidden Markov models (HMM).
- Generate knockoffs for genotype and haplotype data.
- Provides a user-friendly interface for fitting an HMM to genetic data using the software fastPhase.
If you want to learn about applying SNPknock to analyze data from large genome-wide association studies, see KnockoffZoom: https://msesia.github.io/knockoffzoom
Released under the GPL-v3 license - see the file LICENSE in the source distribution.