Question: Multiple Testing Correction
gravatar for ea1402
4.4 years ago by
United States
ea140220 wrote:


I am running couple of different differential expression analysis on my data. I have a quick question that confuses me.

Suppose I am using a lfc threshold of x, when correcting for multiple should I use only the genes that have a lfc greater than my lfc threshold or should I use all the genes regardless of the lfc change? How is this handled in the ebayes with limma?



rnaseq limma moderated t-test • 840 views
ADD COMMENTlink modified 4.4 years ago • written 4.4 years ago by ea140220
Answer: Multiple Testing Correction
gravatar for James W. MacDonald
4.4 years ago by
United States
James W. MacDonald51k wrote:

If you are using a fold change criterion, you should not use multiple corrections simultaneously (well, you can if you want, but using a post hoc adjustment along with multiple comparisons makes the interpretation of the p-values or FDR impossible). If you want to incorporate a fold change, see ?treat.

ADD COMMENTlink written 4.4 years ago by James W. MacDonald51k

Hi James,

thanks for the reply for the limma analysis I am using the treat function. However, I have my own method of calculation p-values for the significance of each comparison. However, considering my data I would like to say a change is statistifically significant whether the fold change is above some threshold. What I was confused was whether to prefilter the data using a fc threshold before multiple correction or do multiple correction first then call the a change statistifically significant if the adj.p.value<0.01 and fc<\theta. I hope i can express the question clearly

ADD REPLYlink written 4.4 years ago by ea140220

If you're not using the p-values from the treat function, then how are you using the treat function? My understanding is that the p-values are the main output from treat.

ADD REPLYlink written 4.4 years ago by Ryan C. Thompson7.4k

Ryan's quite right. The value of the chosen lfc threshold in treat is already incorporated into the p-value that is reported by the function. More specifically, the p-value represents the evidence that the observed log-fold change is significantly different from the specified lfc. There's no need for filtering on the log-fold change before or after the multiple testing correction; just use the reported FDR (i.e., adjusted p-values) directly from topTreat.

ADD REPLYlink modified 4.4 years ago • written 4.4 years ago by Aaron Lun25k
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