correlation among RNAseq and proteomics analysis

Question

[dew]

Dear guys,

May I know possible recommend methods for the correlation analysis among RNAseq and proteomics data? For example, 200 DEGs were identified, 80 DEPs identified, and 50 were overlapped by the RNAseq and proteomics.

So the correlations would be from the 50 overlapped items, right? Thanks a lot!

Answer 1

[tomas4482]

Spearman correlation, pearson correlation or kendall correlation is what you seek for.

[dew]

Thanks a lot!

Answer 2

[qiz218591]

Is there are any numbered parameters that have to be set to see up this correlation, for example, the number of DEGs, the overlapped targets, etc??@tomas4482

[tomas4482]

I've answered the question. Do not ask questions by answering the post. You can either add comment or start a new post. You should search the terms first to understand some basic knowledge about the three analyses.

Your logic is to calculate the amount of overlapped genes, that is, in part, what hypergeometry test does. It tests if genes in a gene list A significantly appear in a given gene list B. Intersection only illustrates the proportion of similarity between two datasets referring to your differential analysis. It did not quantify the correlation.

If you measured expression of 40000 genes using RNA-seq and MS, a dataframe containing scaled average expression of each gene for RNA-seq and MS can be created. Then you can quantify the correlation between RNA-seq and MS.