Package: comorbidPGS 0.4.0

Vincent Pascat

comorbidPGS: Assessing Predisposition Between Phenotypes using Polygenic Scores

Using polygenic scores (PGS, or PRS/GRS for binary outcomes), this package allows to investigate shared predisposition between different conditions, and do fast association analysis, export plots and views of the PGS distribution using 'ggplot2' object.

Authors:Vincent Pascat [aut, cre]

comorbidPGS_0.4.0.tar.gz
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comorbidPGS_0.4.0.tgz(r-4.5-any)comorbidPGS_0.4.0.tgz(r-4.4-any)comorbidPGS_0.4.0.tgz(r-4.3-any)
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comorbidPGS.pdf |comorbidPGS.html✨
comorbidPGS/json (API)

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

Bug tracker:https://github.com/vp-biostat/comorbidpgs/issues

Datasets:

On CRAN:

Conda:

3.78 score 3 stars 3 scripts 172 downloads 9 exports 66 dependencies

Last updated 3 months agofrom:b781cb839b. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 23 2025
R-4.5-winOKMar 23 2025
R-4.5-macOKMar 23 2025
R-4.5-linuxOKMar 23 2025
R-4.4-winOKMar 23 2025
R-4.4-macOKMar 23 2025
R-4.4-linuxOKMar 23 2025
R-4.3-winOKMar 23 2025
R-4.3-macOKMar 23 2025

Exports:assocassocplotcentileplotdecileboxplotdensityplotmr_2slsmr_ratiomultiassocmultiphenassoc

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2gluegtableisobandivreglabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithrzoo