There are four small groups (A, B, C, D), each with 4 students. For the first class period, students are responsible for reading the paper labeled with their small group letter below. For the second class period, one student in the small group will present the paper (see the presentation schedule on ELMS).

Updates: I will try to provide questions to guide the small group discussion and short presentations. This is also a friendly reminder to use pictures in your presentation. These could be figures you make or figures from papers, lecture slides, etc. (cite your source). This greatly helps with everyone's understanding of the material - so thank you!

Sept 22,27: Multiple Sequence Alignment

  1. Jammali et al., 2022, From pairwise to multiple spliced alignment, Bioinformatics Advances. [link]
  2. Shen et al., 2022, WITCH: Improved Multiple Sequence Alignment Through Weighted Consensus Hidden Markov Model Alignment, Journal of Computational Biology. [link] (note there is a related bioRxiv preprint available)
  3. Smirnov and Warnow, 2020, MAGUS: Multiple sequence Alignment using Graph clUStering, Bioinformatics. [link]
  4. Garriga et al., 2019, Large multiple sequence alignments with a root-to-leaf regressive method, Nature Biotechnology. [link]

Oct 20,25: Virus Phylogeny and SARS-CoV-2

  1. Wertheim et al., 2021, Accuracy in Near-Perfect Virus Phylogenies, Systematic Biology. [link]
  2. Li et al., 2020, Phylogenetic supertree reveals detailed evolution of SARS‐CoV‐2, Scientific Reports. [link]
  3. Turakhia et al., 2021, Pandemic-Scale Phylogenomics Reveals The SARS-CoV-2 Recombination Landscape, Nature. [link]
  4. Morel et al., 2020, Phylogenetic Analysis of SARS-CoV-2 Data Is Difficult, Molecular Biology and Evolution. [link]

Nov 3,8: Tumor Phylogeny

  1. Jahn et al., 2016, Tree inference for single-cell data, Genome Biology. [link]
  2. El-Kebir, 2018, SPhyR: tumor phylogeny estimation from single-cell sequencing data under loss and error, Bioinformatics / ECCB 2018. [link]
  3. Malikic et al., 2019, PhISCS: a combinatorial approach for subperfect tumor phylogeny reconstruction via integrative use of single-cell and bulk sequencing data, Genome Research. [link]
  4. Satas et al., 2020, SCARLET: Single-Cell Tumor Phylogeny Inference with Copy-Number Constrained Mutation Losses, Cell Systems / RECOMB 2020. [link]

Nov 29,Dec 1: Phylogenetic Networks

  1. TBD
  2. TBD
  3. TBD
  4. TBD