BRACoD 0.2.0

BRACoD is a method to identify associations between bacteria and physiological variables in Microbiome data

BRACoD

Installation:

pip install BRACoD

If you want to use the R interface, install reticulate in R

Walkthrough

1. Simulate some data and normalize it

   sim_counts, sim_y, contributions = BRACoD.simulate_microbiome_counts(BRACoD.example_otu_data) sim_relab = BRACoD.scale_counts(sim_counts)

2. Run BRACoD

   trace = BRACoD.run_bracod(sim_relab, sim_y, n_sample = 1000, n_burn=1000, njobs=4)

3. Examine the diagnostics

   BRACoD.convergence_tests(trace, sim_relab)

4. Examine the results

   df_results = BRACoD.summarize_trace(trace, sim_counts.columns, 0.3)

5. Compare the results to the simulated truth

   bugs_identified = df_results["bugs"].values bugs_actual = np.where(contributions != 0)[0]

   precision, recall, f1 = BRACoD.score(bugs_identified, bugs_actual) print("Precision: {}, Recall: {}, F1: {}".format(precision, recall, f1))

6. Try with your real data. We have included some functions to help you threshold and process your data df_counts = BRACoD.threshold_count_data(df_counts) df_rel = BRACoD.scale_counts(df_counts) df_rel, Y = remove_null(df_rel, Y) trace = BRACoD.run_bracod(df_rel, Y, n_sample = 1000, n_burn=1000, njobs=4) df_results = BRACoD.summarize_trace(trace, sim_counts.columns, 0.3)