用于药物开发与效应预测的药物孟德尔随机化（Drug-MR）,基于靶蛋白的下游产物（biomarker），以靶蛋白编码基因附近的对biomarker有显著效应的SNP（pQTL或者eQTL）作为工具变量，以biomarker浓度作为暴露，以疾病作为结局，进行孟德尔随机化，以验证蛋白靶对于所研究疾病的影响。

参考资料

资料建议剔除连锁不平衡： R^2 = 0.60

下面是分别用easyMR和MendelR包进行的分析代码

library(easyMR)

dat=get_drug_target_data(
  id = "ieu-b-110",　　　　#暴露GWAS ID
  gene_name="HMGCR",      #药靶蛋白编码基因
  kb=100,          #基因附近的SNP范围
  clump_kb = 100,   #clump的范围
  clump_local = FALSE,
  r2=0.3,   #clump的r2阈值
  pval=0.05,
  MAF = 0.01,  #次等位基因频率 阈值
  build = "GRch38",
  chr = NULL,
  pos_start = NULL,
  pos_end = NULL
)


drug_MR(
  target_gene_data=dat,
  outcome_id ="finn-b-I9_AF",  #疾病GWAS ID
  outcome_name="atrial fibrillation",
  inhibitor = FALSE,
  after_trans_inhibitor = FALSE,
  pval = 0.05,
  action = 2,
  out_type = "binary",
  save_path="e:"
)

library(MendelR)

mr_common(
  id_exposure = "ieu-b-110",  #暴露GWAS ID
  id_outcome = "finn-b-I9_AF",  #疾病GWAS ID
  p1 = 0.05,
  p2 = 0.05,
  write_csv = TRUE,
  write_ppt = FALSE,
  method_list = c("mr_ivw", "mr_egger_regression", "mr_weighted_median",
    "mr_weighted_mode"),
  rm_snps = NULL,
  r2 = 0.3,  #clump的r2阈值
  kb = 100,  #clump的范围
  build_version = "hg19",
  gene = "HMGCR",     #药靶蛋白编码基因
  chr = NULL,
  pos_start = NULL,
  pos_end = NULL,
  eaf_threshold = NULL,
  run_presso = T,
  gene_win = 100,   #基因附近的SNP范围
  NbDistribution = 3000,
  find_proxy = T,
  local_clump = F,
  r2_cal_mode = 1,
  steiger = T,   #是否进行Steiger方向性检验
  auto_ivw = T,
  pop = "EUR",
  no_clump = F,
  out_dir = NULL,
  exposure_samplesize = NULL,
  outcome_samplesize = NULL
)