Lecture with Exercises (Vorlesung mit Übung)

Lecture: Each day from 9:00 to 10:30, usually in room C00.013.

Exercises: Usually Tuesday to Friday from 10:45 to 12:00 and from 1 pm to 5 pm (sometimes 6 pm).

**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)

- Linear Models: slides, R commands for Darwin finches, Darwin finches data, exercises sheet 1, abcdx.txt, bp.txt
- Balanced design ANOVAs, parameter transformations: slides, R-script, exercises sheet 2, bacteria_trainig.txt, bacteria_predict.txt
- Generalized Linear Models: slides, exercise sheet 3, TbDeerAndBoar.txt
- Hotellings T2-test slides, exercise sheet 4, grapes.txt
- Principal Component Analysis (PCA): slides, R-script, exercise sheet 5, HeightShoeWeight.txt EWU.txt
- PCA Regression: slides
- Redundancy Analysis (RDA): slides, R-script, exercise sheet 6, EWU.txt, HSWoutlier.txt, artificialFishes.txt, RIKZGroups.txt
- Correspondence Analysis (CA): slides, R-script, MexicanPlants.txt
- Canonical Correspondence Analysis (CCA): slides, R-script, exercise sheet 7
- Mixed-effects models slides, lme4a.R, mcmcglmm.R, exercise sheet 8, fruits.txt

Material will be added during the course. Here is the course material from 2014.

- 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)
- Mixed effects models in S and S-PLUS / Jose C. Pinheiro ; Douglas M. Bates. (Springer, 2004)

Last update: 13. July 2015