Dear,

In the champ.MVP step, I receive some deltaBeta values of 0.07-0.08 with p-values of 1e-05, but because of the Benjamini-Hochberg correction, my lowest adjusted p-values are 0.9989.

Therefore, I have no significant MVPs and no bedfile is generated for the next step in the pipeline.

Any idea what the problem can be here? Is it recommended to adjust the critical p-value or can I use another correction method?

I did the champ.load and champ.norm appropriately and I am comparing samples from high vs. low physically active people.

Thanks in advance!

> limma=champ.MVP()
The group labels that have been defined CT do not exist in your sample sheet. Please edit the Sample_Group column or the compare.group parameter. ChAMP will use information in your Sample_group columnn.
[1] "contrast low high"
You have found 0 significant MVPs with a BH adjusted P-value below 0.05
No bedfile will be generated for tophits but a full MVP list with all p-values is being saved