Package: MRZero 0.2.0

MRZero: Diet Mendelian Randomization

Encodes several methods for performing Mendelian randomization analyses with summarized data. Similar to the 'MendelianRandomization' package, but with fewer bells and whistles, and less frequent updates. As described in Yavorska (2017) <doi:10.1093/ije/dyx034> and Broadbent (2020) <doi:10.12688/wellcomeopenres.16374.2>.

Authors:Stephen Burgess [aut, cre], Olena Yavorska [aut], James Staley [ctb], Fernando Hartwig [ctb], Jim Broadbent [ctb], Christopher Foley [ctb], Andrew Grant [ctb], Amy Mason [ctb], Ting Ye [ctb], Haoran Xue [ctb], Zhaotong Lin [ctb], Siqi Xu [ctb], Ashish Patel [ctb], Hyunseung Kang [ctb], Sheng Wang [ctb], Ville Karhunen [ctb]

MRZero_0.2.0.tar.gz
MRZero_0.2.0.zip(r-4.5)MRZero_0.2.0.zip(r-4.4)MRZero_0.2.0.zip(r-4.3)
MRZero_0.2.0.tgz(r-4.4-any)MRZero_0.2.0.tgz(r-4.3-any)
MRZero_0.2.0.tar.gz(r-4.5-noble)MRZero_0.2.0.tar.gz(r-4.4-noble)
MRZero_0.2.0.tgz(r-4.4-emscripten)MRZero_0.2.0.tgz(r-4.3-emscripten)
MRZero.pdf |MRZero.html✨
MRZero/json (API)
NEWS

# Install 'MRZero' in R:
install.packages('MRZero', repos = c('https://sb452.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 204 downloads 66 exports 82 dependencies

Last updated 7 months agofrom:cae322f744. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 11 2024
R-4.5-winOKNov 11 2024
R-4.5-linuxOKNov 11 2024
R-4.4-winOKNov 11 2024
R-4.4-macOKNov 11 2024
R-4.3-winOKNov 11 2024
R-4.3-macOKNov 11 2024

Exports:BF_distcalc.rhocalciumcalciumsechdloddschdloddsseci_normalci_tcML_estimatecML_estimate_randomcML_SdThetacondFstatcoursedatadecimalsegger.boundsfastglucfastglucsehdlchdlcseldlcldlcselipid_eaflipid_effectlipid_otherloglikelihoodloglikelihoodcorrelloglikelihoodrhocorrelmbe_bootmbe_estmr_allmethodsmr_clrmr_cMLmr_conmixmr_divwmr_eggermr_forestmr_funnelmr_inputmr_ivwmr_lassomr_loomr_maxlikmr_mbemr_medianmr_mveggermr_mvgmmmr_mvinputmr_mvivwmr_mvivwmemr_mvlassomr_mvmedianmr_mvpcgmmmr_pcgmmmr_pivwmr_plotmv_normpenalised.weightspenalised.weights.deltar.weightsr.weights.deltasimpleCaptrigtrigsevaluesweighted.medianweighted.median.boot.se

Dependencies:askpassbase64encbslibcachemclicodetoolscolorspacecpp11crosstalkcurldata.tableDEoptimRdigestdplyrevaluatefansifarverfastmapfontawesomeforeachfsgenericsggplot2glmnetgluegtablehighrhtmltoolshtmlwidgetshttrisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixMatrixModelsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplotlypromisespurrrquantregR6rappdirsRColorBrewerRcppRcppEigenrlangrmarkdownrobustbasesassscalesshapeSparseMstringistringrsurvivalsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
Data on effect of calcium on fasting glucose (correlated variants)calc.rho calcium calciumse fastgluc fastglucse
CLR ClassCLR-class
Estimate with Regular LikelihoodcML_estimate
Estimate with Regular Likelihood Using Multiple Random Start PointscML_estimate_random
Standard Error of Estimated ThetacML_SdTheta
DIVW ClassDIVW-class
Egger ClassEgger-class
IVW ClassIVW-class
Data on lipid effects on coronary artery disease (uncorrelated variants)chdlodds chdloddsse hdlc hdlcse ldlc ldlcse lipid_eaf lipid_effect lipid_other trig trigse
MaxLik ClassMaxLik-class
Mendelian randomization estimation using all methodsmr_allmethods mr_allmethods,MRInput-method
Conditional likelihood ratio (CLR) methodmr_clr mr_clr,MRInput-method
Constrained maximum likelihood (cML) methodmr_cML mr_cML,MRInput-method
Contamination mixture methodmr_conmix mr_conmix,MRInput-method
Debiased inverse-variance weighted methodmr_divw mr_divw,MRInput-method
MR-Egger methodmr_egger mr_egger,MRInput-method
Draw a forest plot of causal estimatesmr_forest mr_forest,MRInput-method
Draw a funnel plot of variant-specific estimatesmr_funnel mr_funnel,MRInput-method
Inputting and formatting data for use in causal estimationmr_input
Inverse-variance weighted methodmr_ivw mr_ivw,MRInput-method
MR-Lasso methodmr_lasso mr_lasso,MRInput-method
Leave-one-out estimatesmr_loo mr_loo,MRInput-method
Maximum-likelihood methodmr_maxlik mr_maxlik,MRInput-method
Mode-based method of Hartwigmr_mbe mr_mbe,MRInput-method
Median-based methodmr_median mr_median,MRInput-method
Multivariable MR-Egger methodmr_mvegger mr_mvegger,MRMVInput-method
Multivariable generalized method of moments (GMM) methodmr_mvgmm mr_mvgmm,MRMVInput-method
Inputting and formatting data for use in causal estimationmr_mvinput
Multivariable inverse-variance weighted methodmr_mvivw mr_mvivw,MRMVInput-method
Multivariable inverse-variance weighted method with measurement errormr_mvivwme mr_mvivwme,MRMVInput-method
Multivariable MR-Lasso methodmr_mvlasso mr_mvlasso,MRMVInput-method
Multivariable median-based methodmr_mvmedian mr_mvmedian,MRMVInput-method
Multivariable principal components generalized method of moments (PC-GMM) methodmr_mvpcgmm mr_mvpcgmm,MRMVInput-method
Univariable principal components generalized method of moments (PC-GMM) methodmr_pcgmm mr_pcgmm,MRInput-method
Penalized inverse-variance weighted methodmr_pivw mr_pivw,MRInput-method
Draw a scatter plot of the genetic associations and/or causal estimatesmr_plot mr_plot,MRAll-method mr_plot,MRInput-method mr_plot,MRMVInput-method
MRAll ClassMRAll-class
MRcML ClassMRcML-class
MRConMix ClassMRConMix-class
MRHetPen ClassMRHetPen-class
MRInput ClassMRInput-class
MRLasso classMRLasso-class
MRMBE ClassMRMBE-class
MRMVInput ClassMRMVInput-class
MVEgger ClassMVEgger-class
MVGMM ClassMVGMM-class
MVIVW ClassMVIVW-class
MVIVWME ClassMVIVWME-class
MRMVLasso classMVLasso-class
MRMVMedian classMVMedian-class
MVMRcML ClassMVMRcML-class
MVPCGMM ClassMVPCGMM-class
PCGMM ClassPCGMM-class
PIVW ClassPIVW-class
WeightedMedian ClassWeightedMedian-class