check egger

check_egger.R

# library(TwoSampleMR)
library(MRInstruments)
data(gwas_catalog)
gwas_catalog_subset <- subset(gwas_catalog, Phenotype %in% c('Body mass index')& SNP %in% c('rs10938397', 'rs1516725', 'rs2568958', 'rs633715', 'rs7138803', 'rs8089364'))
exposure_dat <- format_gwas_catalog(gwas_catalog_subset)
exposure_dat <- format_data(gwas_catalog_subset, "exposure")
ao <- available_outcomes()
outcome_dat <- extract_outcome_data(exposure_dat$SNP, c(1), proxies = 1, rsq = 0.8, align_alleles = 1, palindromes = 1, maf_threshold = 0.3)
dat <- harmonise_data(exposure_dat, outcome_dat, action = 2)
mr_results <- mr(dat)
mr_forest_plot(mr_singlesnp(dat))


exposure_dat
outcome_dat


ed <- subset(exposure_dat, select=c(SNP, beta.exposure, se.exposure, effect_allele.exposure, other_allele.exposure))
od <- subset(outcome_dat, select=c(SNP, beta.outcome, se.outcome, effect_allele.outcome, other_allele.outcome))


index <- ed$effect_allele.exposure != od$effect_allele.outcome

od$beta.outcome[index] <- od$beta.outcome[index] * -1

summary(lm(od$beta.outcome ~ ed$beta.exposure, weight=1/od$se.outcome^2))