Maximum Likelihood (Part 2: paper discussion)

Previous class check-up

• We studied the algorithms for maximum likelihood and focused on the main contributors to good or poor performance

Learning objectives

At the end of today’s session, you will be able to

• explain in details the RAxML and IQ-Tree inference methods
• use RAxML and IQ-Tree software

Pre-class work

• Read the papers corresponding to your group (in canvas):
  • RAxML1
  • RAxML2
  • IQ-Tree1
  • IQ-Tree2

In-class discussion

Objective: Understand the main algorithms, assumptions and limitations of two widely used maximum likelihood software.

Instructions:

1. Separate group discussions (30 minutes): Students will discuss with their respective groups and prepare a 10-minute presentation for the whole class. Use the software cheatsheet as guideline for your discussion and presentation. Use these google slides:
   • RAxML
   • IQ-Tree
2. Group presentations (20 minutes total; 10 minutes per group): Each group will summarize their discussion in a 10-minute presentation to the class.

Take-home message: always read carefully the paper and the documentation of any phylogenetic method you use

Create your own cheatsheet with description, strengths, weaknesses, assumptions and user choices (and other things you find relevant).