Correcting for batch effects in case-control microbiome studies
Fig 3
Pooling non-normalized samples from different studies can give rise to many spurious associations.
The control group from one study is gradually substituted with randomly chosen control samples from another study (non-normalized, percentile-normalized, limma-corrected, and ComBat-corrected), keeping the total number of case and control samples fixed at n = 40 (see conceptual illustration on the left). Mixing in non-normalized control samples from another study gave rise to spurious results due to batch effects (blue lines). ComBat- and limma-corrected data showed fewer spurious associations (green and red lines). Percentile-normalization showed no increase in spurious results along the titration gradient (orange lines).