Package: mr.simss 0.1.0

Amanda Forde

mr.simss: MR-SimSS: Mendelian Randomisation (MR) method that combats Winner's Curse using a simulated sample splitting approach

Designed to provide users with a method, namely MR-SimSS, which uses simulated sample splitting in order to alleviate Winner's Curse bias in MR causal effect estimates. This approach also takes into account sample overlap between the exposure and outcome genome-wide association studies. It uses summary statistics from genome-wide association studies and works in combination with existing MR methods, such as IVW and MR-RAPS.

Authors:Amanda Forde [aut, cre]

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mr.simss.pdf |mr.simss.html✨
mr.simss/json (API)

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

Peer review:

Bug tracker:https://github.com/amandaforde/mr.simss/issues

On CRAN:

4 exports 4.15 score 116 dependencies 4 scripts

Last updated 11 days agofrom:27d81e0378. Checks:OK: 1 WARNING: 6. Indexed: no.

TargetResultDate
Doc / VignettesOKSep 25 2024
R-4.5-winWARNINGSep 25 2024
R-4.5-linuxWARNINGSep 25 2024
R-4.4-winWARNINGSep 25 2024
R-4.4-macWARNINGSep 25 2024
R-4.3-winWARNINGSep 25 2024
R-4.3-macWARNINGSep 25 2024

Exports:est_lambdamr_simsssplit2split3

Dependencies:abindaskpassbase64encbitbit64bootbslibcachemclicliprcodetoolscolorspaceCompQuadFormcowplotcpp11crayoncrosstalkcurldata.tabledigestdoParalleldplyrevaluatefansifarverfastmapfontawesomeforeachfsgenericsggplot2glmnetglueGPArotationgridExtragtablehighrhmshtmltoolshtmlwidgetshttrieugwasrisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclelme4magrittrMASSmathjaxrMatrixmemoisemetametadatmetaformgcvmimeminqamnormtmr.rapsMRMixMRPRESSOmunsellnlmenloptrnortestnumDerivopensslpbapplypillarpkgconfigplotlyplyrpracmaprettyunitsprogresspromisespsychpurrrR6RadialMRrappdirsRColorBrewerRcppRcppEigenreadrreshape2rlangrmarkdownsassscalesshapestringistringrsurvivalsystibbletidyrtidyselecttinytexTwoSampleMRtzdbutf8vctrsviridisLitevroomwithrxfunxml2yaml

Deriving MR-SimSS

Rendered fromderive-MR-SimSS.Rmdusingknitr::rmarkdownon Sep 25 2024.

Last update: 2024-09-24
Started: 2023-11-07

MR-SimSS: The algorithm

Rendered fromMR-SimSS-algorithm.Rmdusingknitr::rmarkdownon Sep 25 2024.

Last update: 2024-09-25
Started: 2024-09-19

Performing MR-SimSS

Rendered fromperform-MR-SimSS.Rmdusingknitr::rmarkdownon Sep 25 2024.

Last update: 2024-09-24
Started: 2023-11-06

Winner's Curse and weak instrument bias in MR

Rendered fromwc_wib.Rmdusingknitr::rmarkdownon Sep 25 2024.

Last update: 2024-09-19
Started: 2024-09-19