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friendly2MR是孟德尔岁随机化研究中的一个重要补充工具，可以批量探索因素间的因果关系，以及快速填补缺失eaf的数据，但是存在细微差异需要注意。
remotes::install_github("xiechengyong123/friendly2MR")
library(friendly2MR)library(friendly2MR)
#Based on TwosampleMR, to investigate the causal relationship between multiexposure and outcome
a<-find_multiexposure_outcome(exposure =c("ieu-b-6","ieu-b-8","ieu-b-9"),outcome ="ieu-b-4965",write = T,p1 = 5e-08,clump = TRUE,p2 = 5e-08,r2 = 0.001,kb = 10000,LD = 0.8
)
#It can used to investigate the causal relationship between exposure and multioutcome: find_exposure_multioutcome
#It can also used to investigate the causal relationship between multiexposure and multioutcome:
memo<-find_multiexposure_multioutcome_epigraphdb(exposure =c("ukb-a-7"),outcome = c("ieu-a-7"),pval_threshold = 1e-05,write = T,save_path = "multi.csv"
)#Fill in the missing effect allele
library(TwoSampleMR)
aaa<-extract_instruments(outcomes='ukb-b-8755',clump=TRUE, r2=0.001,kb=10000,access_token=NULL)
eaf<-aaa$eaf.exposure
aaa$eaf.exposure<-NA
abc<-find_snp_add_eaf(exposure=aaa)
identical(eaf,abc$eaf.exposure)
#Please pay attention to differences
cb<-cbind(eaf,abc$eaf.exposure)#To find confounders
ee1<-de("ieu-a-7")
confound<-c("body mass index","Coronary heart disease")
expo_dat_nocon<-deletion_confounding_snp(confound = confound,exposure_dat = aaa,query_gene = NULL,query_region = NULL,catalogue = "GWAS",pvalue = 5e-08,proxies = "None",r2 = 0.8,build = 37,write = TRUE,save_path = "MR_ivs.csv"
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