Hello there,

I am a little confused by the toptable output (well really the FDR) and thought I'd quickly check my interpretation.

For the following code:

topall <- toptable(fit, coef="CaseAD", genelist=fit$genes, number=Inf, adjust="fdr", p.value=0.01, lfc=log2(1))

Would the interpretation be:

Using a threshold of 0.05 for FDR adj. p.values and a minimal fold change of 2, this analysis produces n number of genes?

And does the above mean that I would look at the adjusted p.values?

I am interested in following MAQC guidelines for this analysis, so would rather restrict my results to a FDR = 0.05 and p.values < 0.01. However, I am not entirely sure, how to get that, since I am not sure what the "adjust=fdr" relates to here?

Any advice?

Many thanks!!!

Thank you!

Just to clarify: Does that mean my lfc is redundant?

Does that also mean you should plot adjusted p.values instead of p.values?

Yes, your log-fold change threshold is redundant in your original post.

For plotting purposes, it's better to use the

`-log10(p.value)`

, as the enforced monotonicity of the BH correction leads to stretches of genes with the same FDR value, which is not aesthetically pleasing. (For plotting only; calling of DE genes is still done with the FDR.) If you want to visualize the threshold of significance, simply use the largest p-value corresponding to a FDR that is below your threshold. Also check out`volcanoplot`

if that's what you intend to make.Thanks Aaron.

Just to clarify, your lfc is redundant because you set lfc = log2(1) = 0, which is the default and imposes no fold change thresholds on your results, so you are only selecting based on adj. p-values. A fold change of 2 as you indicated would be lfc = 1, but see warning in ?topTable on setting p-val and lfc cutoffs simultaneously, see ?treat and ?topTreat for fold change thresholding.