Schedule

I will update this page before every class with the links to in-class materials and assignments. To view the planned schedule of course activities, view the class calendar using the button below.

Class Calendar

Week 1 (Jan 17, 19)

• Lecture 1: Introduction to Molecular Phylogenetics [slides]
  • Assignment 1 (due 1/19)
• Lecture 2: Trees and characters [notes]
  • Assignment 1 is due.
  • Reading: Allman and Rhodes (2016). Chapter 2: Combinatorics of Trees I.
  • Discussion: Baum et al. (2005). The Tree-Thinking Challenge. Science 310: 979-980.

Week 2 (Jan 24, 26)

• Lecture 3: Homology and Sequence Alignment [notes]
  • Reading: Lemey, Salemi and Vandamme, Chapter 3: 3.1-3.10.
  • Discussion: Fitch (2000). Homology a personal view on some of the problems. TIG 16: 227.
• Computer Lab 1: Introduction to Unix/Multiple Sequence Alignment (MSA).
  • Complete all prerequisites before coming to the class!
  • Post any question you may have on Slack.
  • Assignment 2 (due 02/02)

Week 3 (Jan 31, Feb 2)

• Lecture 4: Parsimony and cladistics. Optimality criteria and character optimization.
  • Reading: Allman and Rhodes (2016). Chapter 3: Parsimony. [notes]
• Lecture 5: Searching tree space. Measures of character fit. Assessing clade support.
  • Reading: Allman and Rhodes (2016). Chapter 9: Tree Space. [notes]
  • Discussion: Baron et al. (2017). A new hypothesis of dinosaur relationships and early dinosaur evolution. Nature 543: 501-506. See also News & Views, Langer et al. communication, and Baron et al. reply.

Week 4 (Feb 7, 9)

• Computer Lab 2: Multiple Sequence Alignment and Parsimony analysis.
  • You may want to install Mafft, PAUP*, and TNT on your computer [links]. However, we will use HPC-class cluster for the excercises.
  • Assignment 3 (due 02/16)
• Lecture 6: Distance matrix methods. Clustering algorithms. [notes]
  • Reading: Allman and Rhodes (2016). Chapter 5: Distance Methods.

Week 5 (Feb 14, 16)

• Lecture 7: NJ algorithm; Model-based distances. [notes]
  • Reading: (Optional!) Allman and Rhodes (2016). Chapter 6: Probabilistic Models of DNA Mutations.
  • Discussion: Naxerova et al. (2017). Origins of lymphatic and distant metastases in human colorectal cancer. Science 357, 55-60.
• Computer Lab 3: Distance analysis with PAUP, PHYLIP, and FastME.
  • Assignment 4 (due 02/28)

Week 6 (Feb 21, 23)

• Lecture 8: Introduction to Maximum Likelihood. [notes]
  • Reading: Allman and Rhodes (2016). Chapter 8: Maximum Likelihood.
• Lecture 9: Constructing Phylogenetic Trees Using Maximum Likelihood. [notes]
  • Discussion: Basem Al-Shayeb et al. (2020). Clades of huge phages from across Earth’s ecosystems. Nature 578, 425–431. If you want to brush up your knowledge on bacteriophages, here is a nice review from the same issue of Nature.

Week 7 (Feb 28, Mar 2)

• Computer Lab 4: Likelihood analysis in RAxML and IQ-Tree.
  • Assignment 5 (due 03/09)
• Lecture 10: Bayes’ theorem and Bayesian methods in phylogenetics. [notes]
  • Reading: Allman and Rhodes (2016). Chapter 12: Bayesian Inference.

Week 8 (Mar 7, 9)

• Lecture 11: Applications of Bayesian methods. [notes]
  • Discussion: Williams et al., 2020. Microbial predators form a new supergroup of eukaryotes Nature, 612:714-719
• Computer Lab 5: Bayesian analysis with MrBayes.
  • Assignment 6 (due 03/23)[dataset]

Spring Break! (Mar 14, 16)

• Don’t forget about your final project outline! (due 3/23)

Week 9 (Mar 21, 23)

• Lecture 12: Model selection and model averaging in Likelihood and Bayesian methods [notes].
  • Reading: Posada & Buckley (2004). Model Selection and Model Averaging in Phylogenetics: Advantages of Akaike Information Criterion and Bayesian Approaches Over Likelihood Ratio Tests. Systematic Biology 53: 793–808.
  • Alternative (simpler) reading: Kelchner & Thomas (2007). Model use in phylogenetics: nine key questions. TREE 22: 87-94
  • Discussion: Abadi et al. 2019. Model selection may not be a mandatory step for phylogeny reconstruction. Nature Communications 10:934
  • There is a critique in BioRxiv if you are interested.
  • Remember to post at least one comment question in the reading-discussion channel on Slack!
• Lecture 13: * Midterm exam review and final project discussion
  • Be ready to present your final project outline. Include hypotheses, data, and proposed methods for the project. In addition, create a GitHub repository for the final project and send me the link.

❗ Midterm exam ❗

• Exam will open on Mar 23, after the class. Will cover weeks 1-8
• Exam will close on Mar 28 before the class.
• You will have one 3hr window to complete the exam.

Week 10 (Mar 28, 30)

• Lecture 14: Neutral and adaptive protein evolution [notes].
  • Reading: Vitti et al. (2013). Detecting Natural Selection in Genomic Data. Annual Review of Genetics 47:97-120.
  • Discussion: Tenaillon et al. (2016). Tempo and mode of genome evolution in a 50,000-generation experiment Nature 536: 165–170.
• Computer Lab 6: Hypotheses testing with PAML.

Week 11 (Apr 4, 6)

• Lecture 15: Gene trees and species trees [notes].
  • Overview: Duchêne (2021). Phylogenomics. Current Biology 31: PR1177-R1181
  • Reading: Mirarab et al. (2021) Multispecies Coalescent: Theory and Applications in Phylogenetics. Annu. Rev. Ecol. Evol. Syst. 2021. 52:247–68
  • Discussion: Romiguier et al. (2022). Ant phylogenomics reveals a natural selection hotspot preceding the origin of complex eusociality. Current Biology 32: 2942-2947.e4
• Lecture 16: Phylogenomics and the tree of life [notes].
• Reading: Kapli et al. (2020) Phylogenetic tree building in the genomic age. Nature Reviews Genetics 21: 428–444
  • Reading (optional): Carter et al. (2023). Estimating phylogenies from genomes: A beginners review of commonly used genomic data in vertebrate phylogenomics. Journal of Heredity 114:1–13
  • Discussion: Simion et al. (2021). To What Extent Current Limits of Phylogenomics Can Be Overcome?. In Scornavacca et al., editors, Phylogenetics in the Genomic Era, chapter No. 2.1, pp. 2.1:1–2.1:34.

Week 12 (Apr 11, 13)

• Computer Lab 7: Phylogenomics.
• Lecture 17: Ancestral State Reconstruction [notes].
  • Reading: Joy et al. 2016. Ancestral reconstruction. PLoS Comput. Biol. 12(7): e1004763
  • Discussion: Starr et al. (2017). Alternative evolutionary histories in the sequence space of an ancient protein. Nature 549:409-413

Week 13 (Apr 18, 20)

• Lecture 18: Phylogenetic comparative methods [notes].
  • Reading: O’Meara (2012). Evolutionary Inferences from Phylogenies: A Review of Methods. Annu. Rev. Ecol. Evol. Syst. 43:267–285.
  • Discussion: Watts et al. 2016. Ritual human sacrifice promoted and sustained the evolution of stratified societies. Nature 532: 228-231.
• Computer Lab 8: BayesTraits.
  • Introductory reading: Pagel and Meade (2006). Bayesian Analysis of Correlated Evolution of Discrete Characters by Reversible-Jump Markov Chain Monte Carlo. Am. Nat. 167:808-825.
  • Final project draft due: share your GitHub/GitLab address with two assigned reviewers. Perform the kind of positive, constructive review you would like to get on your own draft. Prepare your reviews by 4/25.

Week 14 (Apr 25, 27)

• Lecture 18: Timing the evolutionary events [notes].
  • Reading: Bromham et al. (2018). Bayesian molecular dating: opening up the black box. Biological Reviews, 93: 1165-1191
  • Discussion: Worobey et al. (2016). 1970s and “Patient 0” {HIV}-1 genomes illuminate early HIV/AIDS history in North America. Nature 539: 98-101.
    
• Computer Lab 9: Taming the BEAST.
  • Reading (optional): Sauquet (2013). A practical guide to molecular dating. C. R. Palevol 12. 355?367

❗ The final project report is due by the end of the day on Sunday! Submit the link to your GitHub repository on Canvas ❗

Week 15 (May 2, 4): Final presentations

[Scoring rubric]

• 05/02: 9:00-10:45am
  • Momin
  • Cavannah
  • Mahsa
• 05/04: 9:00-10:45am
  • Jordan
  • Dani
  • Alex

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