Question: Pathway analysis from list of differentially expressed genes with fold change, pvalues and normalised expression levels in R
gravatar for reubenmcgregor88
12 days ago by
reubenmcgregor880 wrote:

I have been handed a list of genes from an RNAseq experiment and I have no information about how it was generated as it was done a while ago by a company. I have the lis of genes in columns and pvalues/fold change for different comparisons. I also have the normalised expression values for each gene from each donor.

I have been asked to do some pathway analysis on this and was wondering about the best way to carry this out? I would rather not use arbitrary cut-offs of p-values etc but would rather do some kind of GSEA in R. 

It seems the limma package integrates analyses like camera for this, but am not sure I can simple use the data I have or which format they need to be to use within the limma package?

Any other advice about which packages to use?



ADD COMMENTlink modified 12 days ago by Lluís R300 • written 12 days ago by reubenmcgregor880

How long a list of genes do you have? Do you have just a short list of DE genes or do you have p-values and logFCs for a whole microarray (say)?

ADD REPLYlink written 12 days ago by Gordon Smyth32k

I have a long list of about 20,000, from an array.


ADD REPLYlink written 12 days ago by reubenmcgregor880
gravatar for Lluís R
12 days ago by
Lluís R300
European Union
Lluís R300 wrote:

If you have the sample normalized expression you can load it to R and use camera or other tools in limma, or even other gene set enrichment analysis. However as you have the p-values (and I assume the t-values) you can use fgsea to make a GSEA like the one in Broad Institute webpage using the rank of your genes.

ADD COMMENTlink written 12 days ago by Lluís R300
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