- Handouts
- Lecture videos on phylogenetics
- Lecture videos on computational methods in population genetics
- Exercises on phylogenetics
- Exercises on population genetics

**Language:** English

**Instructors:**

Prof. Dr. Dirk Metzler (lectures and exercises),

Dr. Ulrich Knief
(practical exercises on phylogenetics),

Dr. Ricardo Pereira
(practical exercises on population genetics)

Online-Sessions for questions and exercises will be done via zoom (Meeting-ID: 940 7030 1918; find access key on moodle ) each each

Additional exercises/practicals for block courses Phylogenetics I/II and
Comp. Pop. Gen. I/II: Tuesday 9:00 to 12:00 taught by
Dr. Ulrich Knief
and Dr. Ricardo Pereira.

Note: times for the practicals population genetics taught by Ricardo Pereira
the exact time slots may be subject to change to avoid overlap with other courses.

**Target group (Zielgruppe) and ECTS points:**

Master's and PhD students in EES/MEME, Bioinformatics, Biostatistics, Biology, Mathematics, Statistics,...

Please find the module description for this course
in the official module catalog
of the bioinformatics master's program.

Students can obtain **8 ECTS** for passing the exam of the entire course **Computational Methods in Evolutionary Biology**.

Students in block-structured programms like **EES**, **MEME** and the
Master's program in **Biology** can participate block-wisely.

For **each block**, combined with the additiona practical part,
students can obtain **3 ECTS** by passing the exam and giving a presentation in the practical part.

Phylogenetics I (Block I, 2. Nov. 2020 - 20. Nov. 2020)

Phylogenetics II (Block II, 23. Nov. 2020 - 23. Dec. 2020)

Computational
Methods in Population Genetics I
(Block III, 7. Jan. 2021 - 29. Jan. 2021)

Computational
Methods in Population Genetics II
(Block IV, 1. Feb. 2021 - 17. Feb. 2021)

In the first half of the semester we will focus on computational methods in

Handout on Phylogenetics: PhyloHandout.pdf, handout on Computational Population Genetics: CMPG_handout.pdf

**General Introduction**

Structure of the course and some general remarks
(duration: 19:05 [Min:Sec])

**Classical phylogenetics methods:**

Phylogenetics lectures overview and notations
(26:22)

Distance-based phylogeny reconstruction with UPGA
(37:27)

**Software:** Simple phylogenetic analysis in R and how to use a Linux server
(46:53)

Distance-based phylogeny reconstruction with Neighbor Joining
(28:11)

Parsimony and how to calculate it for a given tree (and given data)
(17:31)

Searching for the most parsimonious tree
(44:30)

Difference measures for phylogenetic trees (14:34)

**Software:** PHYLIP
(33:58)

**Maximum-Likelihood based methods:**

The videos in this section will require some basics
from probability theory.
If you need a brief reminder to the basic terms of probability theory and the
law of total probability you can watch this video:
Basic concepts of probability theory (22:13)

Maximum-likelihood principle and Felsenstein's pruning algorithm (46:02)

**Software:** Seq-gen and a simulation study with phylip (43:06)

The Jukes-Cantor model of sequence evolution (49:25)

Markov chains, their equilibria and reversibility (51:31)

**Software:** maximum-likelihood phylogeny reconstruction an bootstrapping with RAxML (27:36)

Searching for the maximum-likelihood phylogeny (29:34)

Insights from ML for parsimony and distance-based phylogeny (22:50)

Consistency of ML tree reconstruction (22:42)

Bootstrapping (34:14)

**Bayesian sampling with MCMC:**

Bayesian statistics and MCMC (47:03)

MCMCMC and Gibbs sampling (37:34)

**Software:** Bayesian phylogentic analysis with Beast (43:55)

Effective sample sizes in MCMC, problematic priors and mixtures of gene trees (48:43)

**Models for substitution processes in sequence evolution:**

Rate matrices and exponential waiting times (48:20)

Calculating transition matrices (may contain traces of linear algebra) (63:29)

Substitution-rate heterogeneity, relaxed-clock models and time-calibration using fossils (47:46)

**Software:** fossil-based time calibration with BEAST (20:59)

**Quantitative taits and independent contrasts:**

The Brownian motion model for (neutral) quantitive trait evolution and some basics on normally distributed vectors (48:42)

Reduced ML and Felsenstein's prunig algorithm for quantitative traits (44:41)

**Software:** phylip contrasts (8:25)

**Model selection strategies**

Model selection (64:50)

**Statistical Alignment**

Introduction to statistical alignment (69:40)

Statistical alignment with longer gaps (11:55)

Simultaneous sampling of phylogenies and alignments (48:15)

**Statistical Tests for Phylogentic Trees**

The Kishino–Hasegawa Test (13:03)

The Shimodaira–Hasegawa Test (19:14)

The SOWH Test (10:41)

Anisimova and Gascuel's approximate likelihood-ratio test (23:25)

**Phylogenomics and gene families**

Some remarks on phylogenomics and on paralogy and orthology (41:04)

**Introduction to basic models of population genetics**

General remarks, Wright-Fisher model and Kingman's Coalescent (80:02)

Population-scale mutation rate θ, nucleotide diversity and Tajima's D (44:04)

Overview of coalescent-based parameter estimation approaches (27:18)

**Software:** Population genetic data simulation with ms and scrm and summary static calculations with R (44:26)

**Likelihood-based inference with importance sampling and MCMC**

Likelihoods in population genetics and the idea of importance sampling (49:14)

The importance sampling method of B. Griffiths and S. Tavaré (29:20)

LAMARC's approach of using MCMC for Importance Sampling (43:01)

**Software:** A simple LAMARC analysis (52:39)

MCMC sampling of genealogies (60:20)

Ancestral Recombination Graphs and some more aspects of MCMC sampling in LAMARC (40:32)

**Software:** How to simulate data for testing LAMARC (44:51)

MCMC methods for the isolation-migration model as implemented in IM/IMa/IMa2 (54:54)

**Approximate Bayesian Computation (ABC) and other summary-statistics based methods**

ABC with local regression and MCMC without likelihoods (77:35)

**Software: ** an ABC analysis with the abc package in R (41:49)

Sequential/Adaptive ABC (ABC-PMC) (24:08)

Combining summary statistics with partial least squares (42:49)

Composite-likelihood approaches and the Joint site-frequency spectrum (58:40)

**Detecting population structure with programs like STRUCTURE**

Method in STRUCTURE with and without admixture (77:24)

**Software: ** getting started with STRUCTURE (19:20)

STRUCTURE model variants and alternative tools (56:38)

**Selection: Models and statistics**

Basic population genetic model of directional selection (33:53)

Weak selection and the ancestral selection graph (26:35)

Selective sweeps and how they are modeled in simulated in msms (43:18)

Statistics for detecting selective sweeps (33:34)

Soft sweeps, incomplete sweeps and population demography (41:21)

A statistic for detecting balancing selection (30:42)

**Li and Stephens' PAC approach**

The PAC approach (with an excursus on HMMs) (84:25)

phylo02.pdf

phylo03.pdf

phylo04.pdf

phylo05.pdf, pruning.R, PAM_rate_matrix.txt, pfold_rate_matrix.txt

phylo06.pdf, QuantTraitsA.csv, QuantTraitsB.csv, QuantTraitsC.csv, QuantTraits_Tree.txt

phylo07.pdf

phylo08.pdf

sheet02.pdf

sheet03.pdf

sheet04.pdf

sheet05.pdf

sheet06.pdf (updated, now 7 exercises)

sheet07.pdf, cheater.txt, cpg_islands.txt.zip

SortSequences.R (Example R file to convert ms/seq-gen output to Migrate input file, which can be read by Lamarac input file converter)

Announcement for bioinformaticians in official LMU course overview

web page last updated: Dirk Metzler, 13. February 2021