I\'ve found this issue with t-tests and chi-squared in R but I assume this issue applies generally to other tests. If I do:
a <- 1:10
b <- 100:110
t.t
Some R packages solve this issue. The best way is through package pspearman.
source("http://www.bioconductor.org/biocLite.R")
biocLite("pspearman")
library("pspearman")
a=c(1:110,110)
b=1:111
out <- spearman.test(a, b, alternative = "greater", approximation="t-distribution")
out$p.value
[1] 3.819961e-294