Skip to content

SPCompute

1.0.3Package record

Compute Power or Sample Size for GWAS with Covariate Effect

0packages depend
2.8Kdownloads / year
9.5%test coverage
11/13flavors OK

Overview

About

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" arXiv:2203.15641.

Changes in 1.0.3
  • Updated the power (sample size) computation functions to accommodate conditional dependency between covariates.

From NEWS.md in the release

Install

Health

CRAN checks
2NOTE11OK
Check messages
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Ziang Zhang <aguero.zhang@mail.utoronto.ca>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = "Ziang",
                      family = "Zhang",
                      role = c("aut", "cre"),
                      email = "aguero.zhang@mail.utoronto.ca"),
               person(given = "Lei",
                      family = "Sun",
                      role = "aut"))
as necessary.

The Description field contains
  Accounting for Covariate Effects" <arXiv:2203.15641>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

CRAN check page ↗

Slowest check: 4.5 min · r-oldrel-windows-x86_64
Status changes
  • NOTE11 OK, 2 NOTENow
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 1.0.3
READMEYes · 111 wordsVignettesYes · 1 · dynamicNEWSYes · 67% structured · mentions 1.0.3Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
6
Examples that run
100%6 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%
Vignettes (1)

Downloads

2.8K
CRAN downloads in the past year
Rank #18,895 · ~8/day · ~232/mo
Daily download trend is not available in this view yet.
31430 days
70190 days
2.8K1 year
Compare downloads with other packages →
Also on69 r2u5 autocran

Dependencies

Declared dependencies
3 external dependencies (excludes base and recommended)

Installing SPCompute adds no packages beyond those that come with R.

Depends (0)
none
Imports (2)
Matrixstats
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (from the free-text Author field) (2)
· added in 1.0.2

Maintainer since 1.0.1 (2022)

Releases (3)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • 1.0.3Latest
    record
    2023-01-24 · current release · diff ↗
  • 1.0.2
    record
    2022-09-05 · diff ↗ ·
    added 3 exports
    Compute_Power_multi, Compute_Size_multi, convert_preva_to_intercept
  • R
    R 4.2.0 released · 2022-04-22
  • 1.0.1
    record
    2022-04-01
  • R
    R 4.1.0 released · 2021-05-18

Package metadata

First published
2022-04-01
Total releases
3 / 4 yrs
License
GPL (>= 3) OSI
Download size
42 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SPCompute")

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SPCompute version 1.0.3 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →

Privacy choices

These apply to this browser and are stored on this device only. Nothing about your choice is sent to us.

Read the privacy policy