An eight-module course on the computational pipeline behind gut-health
tools like GMWI2 — from a raw sequencer read to a trained,
cross-validated classifier. Parse real sequence data with Biopython,
hand-build a presence/absence matrix, train your own Lasso logistic
regression with scikit-learn, and see exactly how a 2024 published
tool (Mayo Clinic's Gut Microbiome Wellness Index 2) does the same
thing at real scale. Runs natively in-browser; no local installation
required.
Fig. 1 — The pipeline this course builds, stage by stage
01Raw reads
02QC + taxonomy
03Presence / absence
04Health-species score
05Trained classifier
06GMWI2, for real
Each stage above is one or more notebooks in this course — by the time you reach Notebook 06, you've already hand-built every step that a real run of GMWI2 performs automatically.
Nothing to install. Every hands-on notebook here uses
only pandas, numpy, scikit-learn,
and Biopython — all bundled in the in-browser Python
runtime already. No setup cells, no waiting on installs.