# #设置,包括= FALSE ------------------------------------------------ 美元opts_chunk集(缓存= TRUE ) ## ----, eval = FALSE -------------------------------------------------------- ## 库(LeviRmisc) # # df < - geoPmidLookup (c(“GSE26712”,“PMID18593951 ")) ## ------------------------------------------------------------------------ 库(curatedOvarianData)(包= " curatedOvarianData数据 ") ## ------------------------------------------------------------------------ download.file(“https://bitbucket.org/lwaldron/ovrc4_sigvalidation/raw/tip/input/patientselection.config”=“wget”方法,destfile =“patientselection.config”)(“patientselection.config”)归咎于来源。失踪的< -真的keep.common.only < -真的 ## ----, 结果=“隐藏 "---------------------------------------------------- download.file(“https://bitbucket.org/lwaldron/ovrc4_sigvalidation/raw/tip/src/createEsetList_source.R”=“wget”方法,destfile =“createEsetList.R”)(“createEsetList.R来源 ") ## ------------------------------------------------------------------------ 长度(eset ) ## ------------------------------------------------------------------------ runCox < -功能(eset,probeset="CXCL12"){library(survival) eset$y <- Surv(eset$days_to_death, eset$vital_status == "deceased") if(probeset %in% featureNames(eset)){obj <- coxph(eset$y ~ scale(t(exprs(eset[probeset，]))[， 1])) output <- c(obj$coefficients, sqrt(obj$var)) names(output) <- c("log. 12")。其他人力资源”、“SE”)}{零}< -输出}runCox (eset [[1 ]]) ## ------------------------------------------------------------------------ 研究。cofs <- t(sapply(esets, runCox));头(study.coefs ) ## ----, 身高= 5 ---------------------------------------------------------- 图书馆(metafor) res.fe < metafor: rma (yi =研究。Coefs [， 1]， sei=study。[， 2]， method="FE") forest.rma(res。铁、板= gsub(“_eset $”、“rownames (study.coefs)), atransf =实验 ) ## ------------------------------------------------------------------------ ( res.re < - metafor: rma (yi =研究。Coefs [， 1]， sei=study。系数[2],方法= " DL ")) ## ----, eval = TRUE --------------------------------------------------------- 如果(!要求(“survHD”)| | package.version(“survHD”)! =“0.5.0”){图书馆(devtools) install_url (" https://bitbucket.org/lwaldron/survhd/downloads/survHD_0.5.0.tar.gz ")} download.file (destfile = " metaCMA“https://bitbucket.org/lima1/ovrc4_signew/raw/tip/src/metaCMA.R”。R”，method=“wget”)源(“metaCMA.R”)基因。coefs <- metaCMA.coefs(essets)res <- metaCMA. res。选择(eset = eset系数=基因。系数,rma。方法= "铁",n = 200 ) ## ----, eval = TRUE --------------------------------------------------------- 乐多。res <- metaCMA(set,coefs=gene。系数,n = 200, rma.method =“铁”)