CODEWITHSUNDEEP
rsurvival-analysiscox-regression
Huy Nguyen
Huy Nguyen

Reputation: 61

p.value filtration from an lapply-function applied for the function coxph

I'm running the survival analysis for each of expression levels of 566 genes. I did this by combining the function coxph() with the function lapply, and it worked well. Right now, due to the large number of genes considered, I am stuck on how to do P-value filtration in order to only preserve genes with significant survival rates, i.e., when P<0.05.

This is the dummy data:

 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")

After that, to receive the results, please enter the code lines below:

#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)
       })

From here, I'm trying to do P-value filtration as follows:

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

But it is inefficient! Any help would be aprriciated!

Upvotes: 0

Views: 212

Answers (1)

Mohanasundaram
Mohanasundaram

Reputation: 2949

If you are interested in sub-setting the list by any variable (pvalue of logtest in your case), I would suggest the rlist package

library(rlist)

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

This will filter the list by the conditions specified. The conditions can be nested as well.

Upvotes: 1

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