2019 AEESP Workshop - Lecture Slides - Statistical considerations for omic data analysis
My contribution to this years AEESP Conference Workshop Meta-omics in Environmental Engineering Research. Theory, Statistics, and Data Interpretation is a talk titled Statistical considerations for ‘omic data analysis. With such little time to speak, I’m afraid I was only able to scratch the surface, but I hope it was enough to awaken some interest and be of some help!
If so inclined, you can download a pdf of my presentation HERE.
Outline:
- data structures
- transformations and distances
- ordination
- clustering
- Hypothesis testing: PERMANOVA, ANOSIM, & differential abundance testing
I’d like to thank all of my co-organizers for the opportunity to contribute to this project!
Organizers:
- Christopher Anderson, Northeastern University
- Zihan Dai, University of Glasgow
- Christopher Lawson, University of Wisconsin, Madison
- Ameet Pinto, Northeastern University
- Jacob Price, University of Wisconsin, Madison
- Maria Sevillano, Northeastern University
- Varun Srinivasan, Brown and Caldwell
- Ryan Ziels, University of British Columbia