What is the difference between cor and cor.test in R

Question

I have a data frame that its columns are different samples of an experiment. I wanted to find the correlation between these samples. So the correlation between sample v2 and v3, between sample v2 and v4, .... This is the data frame:

> head(t1)
      V2          V3          V4         V5         V6
1 0.12725011 0.051021886 0.106049328 0.09378767 0.17799444
2 0.86096784 1.263327211 3.073650624 0.75607466 0.92244361
3 0.45791031 0.520207274 1.526476608 0.67499102 0.49817761
4 0.00000000 0.001139721 0.003158557 0.00000000 0.00000000
5 0.13383965 0.098943019 0.099922146 0.13871867 0.09750611
6 0.01016334 0.010187671 0.025410170 0.00000000 0.02369374
> nrow(t1)
[1] 23367

if I run the cor function for this data frame to get the correlation between samples(columns) I get NA for all the samples:

> cor(t1, method= "spearman")
V2 V3 V4 V5 V6
V2  1 NA NA NA NA
V3 NA  1 NA NA NA
V4 NA NA  1 NA NA
V5 NA NA NA  1 NA
V6 NA NA NA NA  1

but if I run this :

> cor.test(t1[,1],t1[,2], method="spearman")$estimate
rho 
0.92394 

it is different. Why is this so? What is the correct way of getting correlation between these samples? Thank you in advance.

Answer 1

Your data contains NA values.

From ?cor:

If use is "everything", NAs will propagate conceptually, i.e., a resulting value will be NA whenever one of its contributing observations is NA.

From ?cor.test

na.action a function which indicates what should happen when the data contain NAs. Defaults to getOption("na.action").

On my system:

getOption("na.action")
[1] "na.omit"

Use which(!is.finite(t1)) to search for problematic values and which(is.na(t1)) to search for NA values. cor returns NaN if you have Inf values in your data.