| GWASinlps-package {GWASinlps} | R 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.