The bioBakery help forum

Multiple comparison correcting

Hello, I found this post from a previous conversation in the previous google groups forum that essentially gets exactly at what I want to know and was never answered, so I am hoping to re-open the query here with credit to the original poser of the question Juan Escobar:

"Dear Nicola,

I’m a LEfSe user since long time. My colleagues and I recently submitted a paper with some LEfSe results. One of the reviewers asks us to correct such results for multiple comparisons. I can calculate q-values with R but my question is more fundamental. Do you think it’s necessary to correct for FDR the output of LEfSe? I mean, the algorithm is super strict in choosing biomarkers: first Kruskal-Wallis test to choose features differentially distributed among classes, next pairwise Wilcoxon test applied to the retained features and finally LDA bootstrapping support. FDR control should be performed on each step then. I’m aware of a paper you recently published (Rooks et al. 2014, The ISME Journal) in which you performed Benjamini & Hochberg FDR correction on LEfSe p-values. However, I’m wondering if such correction is necessary altogether.

Your thoughts on this topic are welcomed since as far as I have followed publication of LEfSe results, no one applies FDR.



I am also interested in this topic, the previous thread on google group is:!topic/lefse-users/YB4IVCgZYqY

This thread got no reply for over two years, however, I think many people are interesed in this topic as the LEfSe original paper got citation from over 3000, and more and more papers using LEfSe are published nowadays.

In the section “Subclass structure variants encoding different biological hypotheses” of the original paper, they argued that “In both settings, we explicitly require all the pairwise comparison to reject the null hypothesis for detecting the biomarker; thus, no multiple testing corrections are needed.”. This is the setting in which we perform pair-wise comparison among subclasses, however, if we have no subclasses and only per-feature K-W test were to performed, I think we need to correct the p-value somehow.

As the question from the previous thread stated, many of the paper using LEfSe did not apply corrections of p-value, and biological interpretation of the results would be very different if or not applied correction, any input from the authors is I think helpful.