1. Inferring microbiome networks using graphical models
BY Jared Samilow
Professor Shibu Yooseph

2. A brief point
We can’t just use Pearson’s classical methods (ordinary least squares).
Those methods fail on compositional data, for reasons that are important but beyond the scope of this presentation.
The most important thing is: We can evade many of the problems posed by compositional data by applying a log-ratio transformation to our sample-taxa matrix.

3. Statistical Analysis
Read Aitchison’s seminal work on compositional analysis and did a log-ratio transformation of some microbe data using R. (Shown below)

4. Next Week
Examine results that others have gotten on the same data set to make sure we’re going in the right direction.
Delve more deeply into the math behind the Graphical Lasso technique so that we’ll know how to tweak it for these conditions.
Repeat current code using additive log-ratio transformation and, more difficult, an isometric log-ratio transformation.