SOP 3. Core analyses

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Luke Thompson edited this page Mar 9, 2016 · 4 revisions

Core analyses

Alpha diversity: Calculated per sample, easily parallelizable
Beta diversity: Daniel's parallel block UniFrac is way faster and should work for 7.5M tip tree
Principal coordinates: Now works with up to 50k samples using conda installation of scipy
Taxa summaries: Calculated per sample, easily parallelizable

Extended analyses

GitHub issues -- work on these, add more
Slides from old talks and Google Drive
IPython notebook for plots: Seaborn, Emperor, Qiime results
Group significance: Dependent on specific questions
Machine learning: Somewhat dependent on specific questions
Co-occurrence: Display on the VROOM with Juergen
Phylogenetic trees: ETE, display on the VROOM with Juergen
Other: Yoshiki and Jamie have code/ideas, Bobby Prill meta-analysis