q2-micom provides an interface between Qiime 2 and MICOM.
Analysis of function in microbial communities is often performed based solely on sequencing data and reference genomes. This is a good way to gauge the metabolic potential of a microbiome, but the mere presence of a particular gene does not guarantee a particular metabolic output. For instance, the same E. coli cell can grow either aerobically or anaerobically. However, it will consume and produce very different sets of metabolites in these two environmental settings.
Metabolic modeling tries to estimate the activity of biochemical networks by predicting metabolic fluxes (i.e. the rates of mass conversions within a cell, usually expressed in mmol per gram dry-weight per hour). It uses the genotype and environmental conditions to establish stoichiometry and flux limits for all biochemical reactions within a particular cell and then tries to find sets of fluxes that yield maximum growth under a set of assumptions. This optimization of biomass production under a given stoichiometry is called Flux Balance Analysis (FBA) .
So the gist of it is here:
The best way to get started is by going through our Community Tutorial which will guide you through an analysis of a colorectal cancer data set.
We are particularly interested in additional analysis you would like to perform in order to port them to