  Recent discoveries suggest that our gut microbiome plays an important role in
our health and wellbeing. However, the gut microbiome data are intricate; for
example, the microbial diversity in the gut makes the data high-dimensional.
While there are dedicated high-dimensional methods, such as the lasso
estimator, they always come with the risk of false discoveries. Knockoffs are a
recent approach to control the number of false discoveries. In this paper, we
show that knockoffs can be aggregated to increase power while retaining sharp
control over the false discoveries. We support our method both in theory and
simulations, and we show that it can lead to new discoveries on microbiome data
from the American Gut Project. In particular, our results indicate that several
phyla that have been overlooked so far are associated with obesity.
