Lecture with Exercises (Vorlesung mit Übung)

Lecture: Every day (Mo to Fr) from 9:00 to 10:30 in root C00.013.

Exercises: Plan the rest of each Tuesday to Friday for working on the exercises. Exercise sessions on these days will usually be from 11 to 11:30 am and from 3:30 to 5:00 pm, the latter being in lecture hall B01.027

Exercises: While working on the exercise assignments you can sit in a lab room D00.027.

**Fundamental methods**: Multivariate linear regression, Model Selection, Analysis of Variance (ANOVA), Experimental designs (nested, balanced, unbalanced,...), Graphical Inspection of Fitted Models, Generalized Linear Models (GLM), Mixed Effects Models

R-package: lme4

- Special Methods for complex
**ecological datasets**:

ANCOVA, Redundancy Analysis, Principal Component Analysis (PCA), Canonical Correspondence Analysis,....

R-package: vegan (see also the ecology task view)

- Analysis of
**Gene Expression Data**

Multiple-Testing Problems, Variance-Stabilizing Normalization, Regularization, reconciliation with gene ontologies (GO)...

R-packages: DESeq, vsn, limma, multtest, GOstats

- Special
Methods in Genetics: Mapping
**Quantitative Traits Loci (QTLs)**.

Keywords: Haley-Knott regression, Composite Interval Mapping, Multiple-QTL models,...

R-package: qtl (see also the genetics task view)

- Balanced design ANOVAs, parameter transformations: slides, R-script, exercises sheet 1, abcdx.txt, bp.txt
- Linear Models: slides, R commands for Darwin finches, Darwin finches data, exercises sheet 2, bacteria_trainig.txt, bacteria_predict.txt
- Generalized Linear Models: slides, exercise sheet 3, simulate_data4glm.R, TbDeerAndBoar.txt
- Mixed-effects models slides, lme4a.R, mcmcglmm.R, exercise sheet 8, fruits.txt
- Hotellings T2-test slides, R-script, raspberry.csv, exercise sheet 4, grapes.txt
- Principal Component Analysis (PCA): slides, R-script, exercise sheet 5, HeightShoeWeight.txt, Countries.txt, EWU.txt
- PCA Regression: slides, R-script, RIKZGroups.txt
- Redundancy Analysis (RDA): slides, R-script, exercise sheet 6, HSWoutlier.txt, artificialFishes.txt,
- Genome Wide Association Studies (GWAS): slides, R-script, exercise sheet GWA, PhenoGenoMap.RData, genDataQC.Rdata, GWASfunction.R, 1-getGDS.R, countryOrigin.txt, myGDS,
- QTL Mapping slides, R-script, exercise sheet QTL
- Gene expression slides , rnaseq.R, microarrays.R
- Summary of some (but not all!) essential topics: handout

Material will be added during the course. Here is the course material from 2017.

- Introductory statistics with R / Peter Dalgaard (Springer 2002)
- Biometry: The Principles and Practice of Statistics in Biological Research (3rd Ed.) / Sokal, Rohlf, (Palgrave Macmillan 1995)
- Mixed effects models and extensions in ecology with R / Alain F. Zuur, Elena N. Ieno, N. J. Walker, Anatoly A. Saveliev, Graham M. Smith. (Springer 2009)
- Modern applied statistics with S / W. N. Venables ; B. D. Ripley. - 4. ed. (Springer 2002)
- A Guide to QTL Mapping with R/qtl / Karl W. Broman & Saunak Sen (Springer 2009)
- Analysing ecological data / Alain F. Zuur ; Elena N. Ieno ; Graham M. Smith. (Springer 2007)
- Genetics and analysis of quantitative traits / Michael Lynch ; Bruce Walsh. (Sinauer 1998)
- Introduction to quantitative genetics / D. S. Falconer and Trudy F. C. Mackay. - 4. ed. (Pearson 1996)
- Numerical ecology / Legendre & Legendre (Elsevier 1998)
- Statistical Genetics of Quantitative Traits / Wu, Ma & Casella. (Springer 2007)
- Bioinformatics and Computational Biology Solutions Using R and Bioconductor / R. Gentleman, V.J. Carey, W. Huber, R.A. Irizarry, S. Dudoit (Eds.). (Springer 2005)
- Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics / D. Sorensen, D. Gianola (Springer 2002)
- Mixed effects models in S and S-PLUS / Jose C. Pinheiro ; Douglas M. Bates. (Springer, 2004)

Last update: 24. July 2018