GWASinlps-package: Non-local prior based iterative variable selection tool for...

GWASinlps-packageR Documentation

Non-local prior based iterative variable selection tool for genome-wide association study data, or other high-dimensional data

Description

The GWASinlps package performs variable selection for data from genome-wide association studies (GWAS), or other high-dimensional data with continuous, binary or survival outcomes, combining in an iterative framework, the computational efficiency of the structured screen-and-select variable selection strategy based on some association learning and the parsimonious uncertainty quantification provided by the use of non-local priors (see the References).

Details

Package: GWASinlps
Type: Package
Version: 2.2
Date: 2022-11-22
License: GPL (>= 2)

The main function:
GWASinlps

The main function calls the following functions:
nlpsLM
nlpsGLM
nlpsAFTM

Author(s)

Nilotpal Sanyal <nilotpal.sanyal@gmail.com>

Maintainer: Nilotpal Sanyal <nilotpal.sanyal@gmail.com>

References

Sanyal et al. (2019), "GWASinlps: Non-local prior based iterative SNP selection tool for genome-wide association studies". Bioinformatics, 35(1), 1-11.

Sanyal, N. (2022). "Iterative variable selection for high-dimensional data with binary outcomes". arXiv preprint arXiv:2211.03190.


GWASinlps documentation built on Nov. 23, 2022, 9:06 a.m.