777—Statistical Phylogenetics and Molecular Evolution. [=BIOL 777] (3) (Prereq: grade of B or better in MATH 241 or STAT 510 ) Theory and applications of phylogenetics; estimation via Markov models, likelihood, distances and parsimony; hypothesis testing of evolutionary trees and parameters; related topics including molecular divergence time inference.
Purpose: To familiarize students in both statistics and biology with an increasingly quantitative field of biology, that is, estimating evolutionary trees then studying molecular and morphological evolution using them. Evolutionary trees are a cornerstone of all-evolutionary biology, population genetics, systematics, comparative genomics and bioinformatics. Analysis problems in this field fit naturally into a statistical framework. Molecular evolution is increasingly yielding important information, e.g. in medical sciences, that is difficult or impossible to obtain by direct molecular biology experiments. Students interested in any of the areas mentioned above should find the course important for future research in either academia or industry.
|Introduction— tree terms and definitions; real data and problems; generating simple example data; the Hadamard conjugation||3 weeks|
|Major approaches to inferring trees— parsimony; distance methods; likelihood or predictive methods; Bayesian methods; relationships between methods||3 weeks|
|Reaching for comprehensive models— unequal rates across sites; non-stationary base composition; models for DNA; models for amino acid sequences; using codons; getting away from i.i.d.||2 weeks|
|Model selection and tests— picking models; statistical tests (comparing trees); statistical tests (the evolutionary process)||2 weeks|
|Using trees— tree to tree metrics; consensus techniques; divergence time estimation; matching methods and data||2.5 weeks|
The above course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.
Contact Faculty: None