Class presentation

For your class presentation, you need to pick a paper, read it, present it to the class (with a PDF that will be posted on the class webpage), and answer questions. The presentation should take 15-20 minutes, and will be followed by up to 15 minutes for questions. Your grade on the class presentation will be content and your ability to answer questions (that would be based only on understanding the paper), so don't worry about how pretty your slides are.

You can pick a paper you like, but I will need to approve the choice (I will make sure the paper is within the scope of the course and not too difficult for you to be able to present it). By March 15, send me a list of 2-4 papers you would like to present, along with the hardcopies of the papers; I will select one of these papers. Also, I want everyone to pick a different paper, so if you have requested a paper that someone else has already been approved for, I'll not be able to approve that assignment for you. Therefore, the earlier you send me your requests, the better!

You will need to send me the PDF for your presentation at least one week before the presentation; I will send your presentation back to you with comments, which you can incorporate if you wish. The final presentation (in PDF form) is due 48 hours before your presentation, so I can upload it.

Probably the easiest thing to present is a method addressing something we've studied (or will study). Here is a list of interesting methods that might be good for class presentations.

• ML tree estimation methods: IQtree, RAxML, PhyML, FastTree -2
• Bayesian tree estimation methods (e.g., BEAST, MrBayes, etc.)
• Distance-based tree estimation methods: FastME, NINJA, FastTree (not the same as FastTree-2)
• Multiple sequence alignment methods: Clustal-Omega, Contralign, Muscle, MAFFT, Opal, SATCHMO, PROMALS, PROMALS3D, Prank, Probcons, Probalign, T-COFFEE
• Alignment and tree co-estimation methods: BAli-Phy, Alifritz, and an unnamed method introduced in a PNAS paper by Bouchard-Coté and Jordan
• Multi-locus phylogeny estimation: BEST, *BEAST, GLASS, iGLASS, iGTP, MP-EST, MulRF, PhylDAWG, SMRT-ML, STAR, STEAC, SVDquartets
• Alignment-free phylogeny esimation methods
• Genome rearrangement methods (even just computing the rearrangement distance between two genomes)
• Whole genome alignment (pairwise and multiple are both interesting)
• Phylogenetic networks
• Some genome assembler (e.g., Euler)
• Metagenome taxon identification and abundance profiling (e.g., Carma, Kraken, Megan, Metaphlan, MetaPhyler, NBC, PhyloPythia, Phymm, and PhymmBL)
• Software to correct a gene tree with respect to a species tree (e.g., Notung by Dannie Durand and an unnamed method by Rasmussen and Kellis)
• Software/methods to detect orthology
• Methods to date ancestral nodes in a tree
• Methods to infer ancestral sequences in a tree

Another kind of paper that would be fun to present would be one that addresses some controversial topic (which abound in this area). Some of those topics are:

• Concatenation vs. coalescent-based methods. See, for example, the recent paper in PLoS Currents: Tree of Life (Tonini et al., 2015) and papers by John Gatesy and Mark Springer (most recently in Molecular Phylogenetics and Evolution)
• Concatenation vs. supertree methods
• Restricting data to "good" loci, or using all the loci (see, for example, Rokas et al. Nature 2003, volume 425, number 6960, pages 784-804, and Salichos and Rokas Nature 2013, volume 497, number 7449, pages 327-331)
• The role of morphology vs. molecular sequence data
• Can trees be reconstructed in the presence of horizontal gene transfer? (See Gogarten et al. Molecular Biology and Evolution Volume 19, pages 2226-2238, 2002, and discussion and other cited papers in Roch and Snir, Journal of Computational Biology 20(2):93-112, 2013.)

Another type of paper that would be of interest is one that addresses the use of these methods to answer some biological problem. If this is of interest to you, please talk to me about what you would want to present.