## ----------------------------------------------------------------------------- library(MendelianRandomization) # loading the package ## ----------------------------------------------------------------------------- MRInputObject <- mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse) MRInputObject # example with uncorrelated variants MRInputObject.cor <- mr_input(bx = calcium, bxse = calciumse, by = fastgluc, byse = fastglucse, corr = calc.rho) MRInputObject.cor # example with correlated variants ## ----eval=FALSE--------------------------------------------------------------- # MRInputObject <- mr_input(ldlc, ldlcse, chdlodds, chdloddsse) ## ----------------------------------------------------------------------------- IVWObject <- mr_ivw(MRInputObject, model = "default", robust = FALSE, penalized = FALSE, correl = FALSE, weights = "simple", psi = 0, distribution = "normal", alpha = 0.05) IVWObject <- mr_ivw(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse)) IVWObject IVWObject.correl <- mr_ivw(MRInputObject.cor, model = "default", correl = TRUE, distribution = "normal", alpha = 0.05) IVWObject.correl <- mr_ivw(mr_input(bx = calcium, bxse = calciumse, by = fastgluc, byse = fastglucse, corr = calc.rho)) IVWObject.correl ## ----------------------------------------------------------------------------- WeightedMedianObject <- mr_median(MRInputObject, weighting = "weighted", distribution = "normal", alpha = 0.05, iterations = 10000, seed = 314159265) WeightedMedianObject <- mr_median(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse)) WeightedMedianObject SimpleMedianObject <- mr_median(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse), weighting = "simple") SimpleMedianObject ## ----------------------------------------------------------------------------- EggerObject <- mr_egger(MRInputObject, robust = FALSE, penalized = FALSE, correl = FALSE, distribution = "normal", alpha = 0.05) EggerObject <- mr_egger(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse)) EggerObject EggerObject.corr <- mr_egger(MRInputObject.cor, correl = TRUE, distribution = "normal", alpha = 0.05) EggerObject.corr <- mr_egger(mr_input(bx = calcium, bxse = calciumse, by = fastgluc, byse = fastglucse, corr = calc.rho)) EggerObject.corr ## ----------------------------------------------------------------------------- MaxLikObject <- mr_maxlik(MRInputObject, model = "default", correl = FALSE, psi = 0, distribution = "normal", alpha = 0.05) MaxLikObject <- mr_maxlik(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse)) MaxLikObject MaxLikObject.corr <- mr_maxlik(mr_input(bx = calcium, bxse = calciumse, by = fastgluc, byse = fastglucse, corr = calc.rho)) MaxLikObject.corr ## ----------------------------------------------------------------------------- MBEObject <- mr_mbe(MRInputObject, weighting = "weighted", stderror = "delta", phi = 1, seed = 314159265, iterations = 10000, distribution = "normal", alpha = 0.05) MBEObject <- mr_mbe(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse)) MBEObject ## ----eval = FALSE------------------------------------------------------------- # HetPenObject <- mr_hetpen(MRInputObject, # prior = 0.5, # CIMin = -1, # CIMax = 1, # CIStep = 0.001, # alpha = 0.05) ## ----------------------------------------------------------------------------- HetPenObject <- mr_hetpen(mr_input(bx = ldlc[1:10], bxse = ldlcse[1:10], by = chdlodds[1:10], byse = chdloddsse[1:10]), CIMin = -1, CIMax = 5, CIStep = 0.01) HetPenObject ## ----------------------------------------------------------------------------- bcrp =c(0.160, 0.236, 0.149, 0.09, 0.079, 0.072, 0.047, 0.069) bcrpse =c(0.006, 0.009, 0.006, 0.005, 0.005, 0.005, 0.006, 0.011) bchd =c(0.0237903, -0.1121942, -0.0711906, -0.030848, 0.0479207, 0.0238895, 0.005528, 0.0214852) bchdse =c(0.0149064, 0.0303084, 0.0150552, 0.0148339, 0.0143077, 0.0145478, 0.0160765, 0.0255237) HetPenObject.multimode <- mr_hetpen(mr_input(bx = bcrp, bxse = bcrpse, by = bchd, byse = bchdse)) HetPenObject.multimode ## ----------------------------------------------------------------------------- ConMixObject <- mr_conmix(MRInputObject, psi = 0, CIMin = NA, CIMax = NA, CIStep = 0.01, alpha = 0.05) ConMixObject <- mr_conmix(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse)) ConMixObject ## ----------------------------------------------------------------------------- LassoObject <- mr_lasso(MRInputObject, distribution = "normal", alpha = 0.05, lambda = numeric(0)) LassoObject <- mr_lasso(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse)) LassoObject ## ----------------------------------------------------------------------------- DIVWObject <- mr_divw(MRInputObject, over.dispersion = TRUE, alpha = 0.05, diagnostics = FALSE) DIVWObject <- mr_divw(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse)) DIVWObject ## ----------------------------------------------------------------------------- PIVWObject <- mr_pivw(MRInputObject, over.dispersion = TRUE, delta = 0, sel.pval = NULL, Boot.Fieller = TRUE, alpha = 0.05) PIVWObject <- mr_pivw(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse)) PIVWObject ## ----eval=FALSE--------------------------------------------------------------- # cMLObject <- mr_cML(MRInputObject, # MA = TRUE, # DP = TRUE, # K_vec = 0:(length(object@betaX)-2), # random_start = 0, # num_pert = 200, # random_start_pert = 0, # maxit = 100, # random_seed = 314, # n, # Alpha = 0.05) ## ----------------------------------------------------------------------------- cMLObject <- mr_cML(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse), n = 17723) cMLObject ## ----eval=FALSE--------------------------------------------------------------- # pcGMMObject <- mr_pcgmm(MRInputObject.cor, # nx, # ny, # r = NULL, # thres = 0.999, # robust = TRUE, # alpha = 0.05) ## ----------------------------------------------------------------------------- pcGMMObject <- mr_pcgmm(mr_input(bx = calcium, bxse = calciumse, by = fastgluc, byse = fastglucse, corr = calc.rho), nx=6351, ny=133010) pcGMMObject ## ----------------------------------------------------------------------------- MVMRInputObject <- mr_mvinput(bx = cbind(ldlc, hdlc, trig), bxse = cbind(ldlcse, hdlcse, trigse), by = chdlodds, byse = chdloddsse) MVMRInputObject MVMRInputObject.cor <- mr_mvinput(bx = cbind(ldlc, hdlc, trig), bxse = cbind(ldlcse, hdlcse, trigse), by = chdlodds, byse = chdloddsse, correlation = diag(length(ldlc))) ## ----------------------------------------------------------------------------- MVIVWObject <- mr_mvivw(MVMRInputObject, model = "default", correl = FALSE, correl.x = NULL, nx = NA, distribution = "normal", alpha = 0.05) MVIVWObject <- mr_mvivw(MVMRInputObject) MVIVWObject ## ----------------------------------------------------------------------------- MVIVWObject.condF <- mr_mvivw(MVMRInputObject, nx = 17723) MVIVWObject.condF ## ----------------------------------------------------------------------------- MVEggerObject <- mr_mvegger(MVMRInputObject) MVEggerObject MVMedianObject <- mr_mvmedian(MVMRInputObject) MVMedianObject MVLassoObject <- mr_mvlasso(MVMRInputObject) MVLassoObject MVcMLObject <- mr_mvcML(MVMRInputObject, n = 17723) MVcMLObject MVGMMObject <- mr_mvgmm(MVMRInputObject, nx=rep(17723,3), ny=17723) MVGMMObject MVpcGMMObject <- mr_mvpcgmm(MVMRInputObject.cor, nx=rep(17723,3), ny=17723) MVpcGMMObject ## ----------------------------------------------------------------------------- MRInputObject <- mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse) MRAllObject_all <- mr_allmethods(MRInputObject, method = "all") MRAllObject_all MRAllObject_egger <- mr_allmethods(MRInputObject, method = "egger") MRAllObject_egger MRAllObject_main <- mr_allmethods(MRInputObject, method = "main") MRAllObject_main ## ----eval = FALSE------------------------------------------------------------- # mr_plot(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse), # error = TRUE, orientate = FALSE, line = "ivw") ## ----------------------------------------------------------------------------- mr_plot(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse), error = TRUE, orientate = FALSE, line = "ivw", interactive = FALSE) ## ----------------------------------------------------------------------------- mr_plot(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse), error = TRUE, orientate = FALSE, line = "ivw", interactive = FALSE, labels = TRUE) ## ----------------------------------------------------------------------------- mr_plot(MVMRInputObject, interactive = FALSE) ## ----------------------------------------------------------------------------- mr_plot(MRAllObject_all) ## ----------------------------------------------------------------------------- mr_plot(MRAllObject_egger) ## ----------------------------------------------------------------------------- mr_plot(mr_allmethods(mr_input(bx = hdlc, bxse = hdlcse, by = chdlodds, byse = chdloddsse))) ## ----------------------------------------------------------------------------- mr_forest(MRInputObject, ordered=TRUE) ## ----------------------------------------------------------------------------- mr_forest(MRInputObject, methods = c("ivw", "median", "wmedian", "egger", "maxlik", "mbe", "conmix"), snp_estimates = FALSE) ## ----------------------------------------------------------------------------- mr_funnel(mr_input(bx = ldlc[1:8], bxse = ldlcse[1:8], by = chdlodds[1:8], byse = chdloddsse[1:8])) ## ----------------------------------------------------------------------------- mr_loo(MRInputObject) ## ----eval=FALSE--------------------------------------------------------------- # library(ggplot2) # forest = mr_forest(mr_input(ldlc, ldlcse, chdlodds, chdloddsse)) # forest2 = forest + coord_cartesian(xlim=c(-5,5)) # forest2 ## ----eval = FALSE------------------------------------------------------------- # mr_ivw(pheno_input(snps=c("rs12916", "rs2479409", # "rs217434", "rs1367117", # "rs4299376", "rs629301", # "rs4420638", "rs6511720"), # exposure = "Low density lipoprotein", # pmidE = "24097068", # ancestryE = "European", # outcome = "Coronary artery disease", # pmidO = "26343387", # ancestryO = "Mixed"))