The posed linear programming problems can result in multiple equivalent solutions.
Use the ensemble flag to generate a user-defined number of equally plausible models to be stored in a single sbml file, e.g. -n 100.
One can then calculate the pairwise Jaccard distance between models within ensembles to quantify network uncertainity.
Unless you submit jobs in parallel on the cluster it will not be feasible to generate all results within the timeframe of this course. The following code demonstrates how the ensemble models were precomputed for the different datasets. You do not need to generate results for each community, as all results are pre-computed in their respective directories.
$ while read model;
do carve -v --cobra -n 100 -o $ROOT/ensembles/${model}_ensemble.xml $ROOT/genomes/$COMM/${model}.faa;
done< <(ls $ROOT/genomes/$COMM|sed 's/.faa//g')- Why can there be differences between models generated from the same genome file?
- How does the ensemble carving process work?
- How can ensembles be useful for understanding network uncertainty?