Extract lower limit of pvalue less than 2.2*10^-16

Question

[titua19810]

Hi,

I am using linear mixed model to get p values that are used to plot graph . The R package that I am using for the model is multcomp and the function that is used from multcomp package is glht. From the output I get some pvalues that are less than 2. 210^-16 but in the output it is shown as value of 0. I need to extract the exact p values for pvalues less than 2.210^-16 instead of 0's.

The following command are used to run the model and I extraced p values from the summary(model) in R

test <- xyz[1:115000,]
test$group <- rep(1:1000, each=115)

ngroup = max(test$group)

#code within tryCatch will proceed to next iteration even if error
pvals_drug_1 <- matrix(rep(-1,ngroup*6), nrow=ngroup, ncol=6)
pvals_time_1 <- matrix(rep(-1,ngroup*4), nrow=ngroup, ncol=4)
pvals_omni_interaction_1<- matrix(rep(-1,ngroup*1), nrow=ngroup, ncol=1)
for (i in 1:ngroup) {
    tryCatch ({
        m1 <- lmer(ratio ~ conc*week + (1|pool/cell), data=subset(test, test$group==i))
        s1 <- glht(m1, linfct=c("conc + 1*conc:week == 0",
                                              "conc + 2*conc:week == 0",
                                              "conc + 3*conc:week == 0",
                                              "conc + 4*conc:week == 0",
                                              "conc + 6*conc:week == 0",
                                              "conc + (3.2)*conc:week==0"))
    s2 <- glht(m1, linfct=c("week  == 0",
                                           "week + 8*conc:week == 0",
                                           "week + 25*conc:week == 0",
                                           "week + 75*conc:week == 0"))

   pvals_drug_1[i,] <- summary(s1)$test$pvalues[1:6]
   pvals_time_1[i,] <- summary(s2)$test$pvalues[1:4]
   pvals_omni_interaction_1[i,]<- summary(m1)[[10]][20]
  }, error=function(e){cat("Error on line ", i, ": ", conditionMessage(e), "\n")})
 }

I would highly appreciate if anybody can guide me how to exact pvalues that are less than 2.2*10^-16 so that I can make a QTL plot with right hieght of the peaks of multiple hypothesis adjusted -logQ values against human genome.

Answer 1

[Devon Ryan]

I'll just link this older cross-validated thread, which largely summarizes things.