  Microbiome research is now moving beyond the compositional analysis of
microbial taxa in a sample. Increasing evidence from large human microbiome
studies suggests that functional consequences of changes in the intestinal
microbiome may provide more power for studying their impact on inflammation and
immune responses. Although 16S rRNA analysis is one of the most popular and a
cost-effective method to profile the microbial compositions, marker-gene
sequencing cannot provide direct information about the functional genes that
are present in the genomes of community members. Bioinformatic tools have been
developed to predict microbiome function with 16S rRNA gene data. Among them,
PICRUSt2 has become one of the most popular functional profile prediction
tools, which generates community-wide pathway abundances. However, no
state-of-art inference tools are available to test the differences in pathway
abundances between comparison groups. We have developed ggpicrust2, an R
package, to do extensive differential abundance(DA) analyses and provide
publishable visualization to highlight the signals.
