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gwrpvr  

Genome-Wide Regression P-Value (Gwrpv)
View on CRAN: Click here


Download and install gwrpvr package within the R console
Install from CRAN:
install.packages("gwrpvr")

Install from Github:
library("remotes")
install_github("cran/gwrpvr")

Install by package version:
library("remotes")
install_version("gwrpvr", "1.0")



Attach the package and use:
library("gwrpvr")
Maintained by
Michael O'Neill
[Scholar Profile | Author Map]
First Published: 2017-10-19
Latest Update: 2017-10-19
Description:
Computes the sample probability value (p-value) for the estimated coefficient from a standard genome-wide univariate regression. It computes the exact finite-sample p-value under the assumption that the measured phenotype (the dependent variable in the regression) has a known Bernoulli-normal mixture distribution. Finite-sample genome-wide regression p-values (Gwrpv) with a non-normally distributed phenotype (Gregory Connor and Michael O'Neill, bioRxiv 204727 ).
How to cite:
Michael O'Neill (2017). gwrpvr: Genome-Wide Regression P-Value (Gwrpv). R package version 1.0, https://cran.r-project.org/web/packages/gwrpvr. Accessed 05 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited gwrpvr R package
View gwrpvr citation profile
Other R packages that gwrpvr depends, imports, suggests or enhances
Complete documentation for gwrpvr
Functions, R codes and Examples using the gwrpvr R package
Some associated functions: calc_pvalue . close_to_normal . gwrpv . gwrpv_batch . gwrpvr . highlow . loop_calc_pvalue . regresults . 
Some associated R codes: gwrpv.R .  Full gwrpvr package functions and examples
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