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SPCompute
View on CRAN: Click
here
Download and install SPCompute package within the R console
Install from CRAN:
install.packages("SPCompute")
Install from Github:
library("remotes")
install_github("cran/SPCompute")
Install by package version:
library("remotes")
install_version("SPCompute", "1.0.3")
Attach the package and use:
library("SPCompute")
Maintained by
Ziang Zhang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-04-01
Latest Update: 2023-01-24
Description:
Fast computation of the required sample size or the achieved power, for GWAS studies with different types of covariate effects and different types of covariate-gene dependency structure. For the detailed description of the methodology, see Zhang (2022) "Power and Sample Size Computation for Genetic Association Studies of Binary Traits: Accounting for Covariate Effects" <doi:10.48550/arXiv.2203.15641>.
How to cite:
Ziang Zhang (2022). SPCompute: Compute Power or Sample Size for GWAS with Covariate Effect. R package version 1.0.3, https://cran.r-project.org/web/packages/SPCompute. Accessed 22 Dec. 2024.
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Other R packages that SPCompute depends,
imports, suggests or enhances
Complete documentation for SPCompute
Functions, R codes and Examples using
the SPCompute R package
Some associated functions: Compute_Power . Compute_Power_multi . Compute_Size . Compute_Size_multi . check_parameters . convert_preva_to_intercept .
Some associated R codes: 01_single_E.R . 02_multiple_E_binary_trait.R . 03_multiple_E_continuous_trait.R . 04_multiple_E_binary_trait_dep.R . 05_multiple_E_continuous_trait_dep.R . 06_wrapper.R . Full SPCompute package functions and examples
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