Package: winnerscurse 0.1.1

Amanda Forde

winnerscurse: Winner's Curse Adjustment Methods for Summary Statistics from Genome-Wide Association Studies

Designed to provide users with easy access to published methods which aim to correct for Winner's Curse using only summary statistics from genome-wide association studies. With merely estimates of effect size and associated standard error for each genetic variant, users are able to implement these methods to obtain more accurate estimates of the true effect sizes. These methods can be applied to data from both quantitative and binary traits.

Authors:Amanda Forde [aut, cre]

winnerscurse_0.1.1.tar.gz
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winnerscurse_0.1.1.tgz(r-4.4-any)winnerscurse_0.1.1.tgz(r-4.3-any)
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winnerscurse.pdf |winnerscurse.html
winnerscurse/json (API)

# Install 'winnerscurse' in R:
install.packages('winnerscurse', repos = c('https://mrcieu.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/amandaforde/winnerscurse/issues

Pkgdown:https://amandaforde.github.io

On CRAN:

4.18 score 5 stars 2 scripts 10 exports 21 dependencies

Last updated 9 months agofrom:2ed00bb119. Checks:OK: 1 NOTE: 4 ERROR: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 02 2024
R-4.5-winNOTEDec 02 2024
R-4.5-linuxNOTEDec 02 2024
R-4.4-winNOTEDec 02 2024
R-4.4-macERRORDec 02 2024
R-4.3-winNOTEDec 02 2024
R-4.3-macERRORDec 02 2024

Exports:BR_sscl_intervalconditional_likelihoodcondlike_repempirical_bayesFDR_IQTMSE_minimizerse_adjustsim_statsUMVCUE

Dependencies:clidplyrfansigenericsgluelatticelifecyclemagrittrMatrixmgcvnlmepillarpkgconfigR6rlangscamtibbletidyselectutf8vctrswithr

Methods for use with discovery and replication GWASs

Rendered fromdiscovery_replication.Rmdusingknitr::rmarkdownon Dec 02 2024.

Last update: 2023-12-06
Started: 2021-03-18

Methods for use with discovery GWAS

Rendered fromwinners_curse_methods.Rmdusingknitr::rmarkdownon Dec 02 2024.

Last update: 2023-12-06
Started: 2021-02-03

Standard errors and confidence intervals of adjusted estimates

Rendered fromstandard_errors_confidence_intervals.Rmdusingknitr::rmarkdownon Dec 02 2024.

Last update: 2023-12-06
Started: 2021-03-09