SNPknock documentation¶

Introduction¶

SNPknock is a Python library for generating knockoff variables from discrete Markov chains and hidden Markov models, with specific support for genomic data. See also the corresponding R package.

This package implements the algorithms for knockoff generation described in:

“Gene hunting with hidden Markov model knockoffs”, Sesia et al., Biometrika, 2019, (doi:10.1093/biomet/asy033).

“Multi-resolution localization of causal variants across the genome”, Sesia et al., bioRxiv, 2019, (doi: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.

SNPknock documentation¶

Introduction¶

Source code¶

Getting started¶

Indices¶

Table Of Contents