R p、 应用于函数coxph的lappy函数的值过滤

我正在对566个基因的每个表达水平进行生存分析。我通过将coxph函数与lappy函数结合起来实现了这一点，它运行得很好。现在，由于考虑了大量的基因，我一直在研究如何进行P值过滤，以便只保留具有显著存活率的基因，即，当P

时，如果您有兴趣在您的案例中通过logtest的任何变量pvalue来设置列表，我建议使用rlist包

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这将根据指定的条件筛选列表。条件也可以嵌套。

我无法复制您的列表并获取错误，类型为“closure”的对象不可用subsettable@Mohanasundaram谢谢你的警告！这是我的错，我改正了。请再次复习并帮助我。谢谢我看到了p值过滤的请求，并认为我是在寻找随机积分的请求。

 df1 = structure(list(ERLIN2 = structure(c(`TCGA-A1-A0SE-01` = 1L, `TCGA-A1-A0SH-01` = 1L, 
`TCGA-A1-A0SJ-01` = 1L), .Label = c("down", "up"), class = "factor"), 
    BRF2 = structure(c(`TCGA-A1-A0SE-01` = 2L, `TCGA-A1-A0SH-01` = 1L, 
    `TCGA-A1-A0SJ-01` = 2L), .Label = c("down", "up"), class = "factor"), 
    ZNF703 = structure(c(`TCGA-A1-A0SE-01` = 2L, `TCGA-A1-A0SH-01` = 1L, 
    `TCGA-A1-A0SJ-01` = 2L), .Label = c("down", "up"), class = "factor"), 
    time = c(43.4, 47.21, 13.67), event = c(0, 0, 0)), row.names = c("TCGA-A1-A0SE-01", 
"TCGA-A1-A0SH-01", "TCGA-A1-A0SJ-01"), class = "data.frame")

#library
if(!require(survival)) install.packages('survival')
library('survival')

#run survival analysis
df2=lapply(c("ERLIN2",    "BRF2",      "ZNF703"),

       function(x) {

         formula <- as.formula(paste('Surv(time,event)~',as.factor(x)))
         coxFit <- coxph(formula, data = df1)
         summary(coxFit)
       })

for (i in 3){
    df2 = df2 %>% subset(df2[[i]]$logtest[3] < 0.05)
}

library(rlist)

df3 <-  list.filter(df2, logtest[["pvalue"]] < 0.05)