calculate p-value for the r pairwise

Question

[Edalat]

hello all,

I calculated correlation by this function for control and tumor:

control.corr=cor(cod[grep(".C",cod$name),-1],nc[grep(".C",nc$name),-1],method = "spearman") tumor.corr=cor(cod[grep(".T",cod$name),-1],nc[grep(".T",nc$name),-1],method = "spearman")

so I have two matrix of r pairwise, now I want calculate p-value for the r's, what should I do?

Answer 1

[andrew.j.skelton73]

cor.test()

[EagleEye]

To be specific,

control.corrP=cor.test(cod[grep(".C",cod$name),-1],nc[grep(".C",nc$name),-1],method = "spearman")$p.value 

tumor.corrP=cor.test(cod[grep(".T",cod$name),-1],nc[grep(".T",nc$name),-1],method = "spearman")$p.value

[Edalat]

thank you,this is what I want ;-)

[Edalat]

control.corrP=cor.test(coding.rpkm[grep("23.C",coding.rpkm$name),-1],ncoding.rpkm[grep("23.C",ncoding.rpkm$name),-1],method = "spearman")$p.value

Error in cor.test.default(coding.rpkm[grep("23.C", coding.rpkm$name), : 'x' and 'y' must have the same length

there is an error,why? it is clear that the number of coding and ncoding are not same.

[Sam]

The length of coding.rpkm[grep("23.C",coding.rpkm$name),-1] vector differs from the length of ncoding.rpkm[grep("23.C",ncoding.rpkm$name),-1] vector. You'll need to make sure both vector are of the same length

[Edalat]

yes the number of genes in coding and noncoding are different and with this difference I calculate correlation,how can I do that?!

[Sam]

how can you perform a pairwise correlation if you don't have data of equal length? You won't even have the pairwise R, right?

[EagleEye]

I think in your case correlation analysis will not be meaningful. I can suggest t-test or Kruskal Wallis statistics.

Note: if you have more number of samples (example 10), you can use correlation of individual coding and noncoding expression with respect to 10 samples ( this will make sense because you will have same number of samples in both case).