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Korbinian Strimmer and Steve Hoffmann
University of Leipzig, Summer Term 2012

Starts: 18 April 2012
Time: Wednesday 13:30-15:00
Place: IZBI Seminarraum 109, Härtelstr. 16-18


In summer term 2012 the seminar "Current Topics in Biostatistics" will be concerned with statistical techniques for the analysis of RNA-Seq data. These data sets are now frequently encountered in transcriptome analysis and replace data from earlier technologies, such as microarrays.

A "Schein" will be awarded on the basis of a presentation and active discussion (5 LP for 2 SWS seminar + 1 SWS tutorial).


The first meeting is on 18 April 2012. We then meet regularly on Wednesday afternoon (sessions 1-4) and Tuesday afternoon (sessions 5-10). Every Thursday morning 11-12 there is also a tutorial to discuss each paper prior to the presentation in the seminar.


Session Date Topic Paper(s) Presenter
1 Wednesday 18 April 2012 Next-generation DNA sequencing (+ videos) 1, 2 Diana Le Duc
2 Wednesday 25 April 2012 RNA-Seq analysis 3, 4 Markus Kreuz
3 Wednesday 2 May 2012 Experimental design 5 Lorena Rivarola Duarte
4 Wednesday 9 May 2012 Expression quantification I 6, 7 Mario Fasold
5 Tuesday 15 May 2012 Expression quantification II 8, 9 Helene Kretzmer
6 Tuesday 22 May 2012 Normalization and differential expression I 10,11 Jens Gietzelt
7 Tuesday 29 May 2012 Normalization and differential expression II 12,13 Katharina Hößel
8 Tuesday 5 June 2012 Classification and clustering 14 Verena Zuber
9 Tuesday 12 June 2012 Multiple testing 15 Bernd Klaus
10 Tuesday 19 June 2012 Genetic networks 16 Korbinian Strimmer


  1. J. Shendure and H. Ji. 2008. Next-generation DNA sequencing. Nature Biotechnology 26:1135-1145.
  2. M. L. Metzger. 2010. Sequencing technologies - the next generation. Nature Reviews Genetics. 11:31-46.
  3. Z. Wang et al. 2009. RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics. 10:57-63.
  4. A. C. Frazee et al. 2011. ReCount: a multi-experiment resource of analysis-ready RNA-seq gene count data sets. BMC Bioinformatics 12:449.
  5. P. L. Auer and R. W. Doerge. 2010. Statistical design and analysis of RNA sequencing data. Genetics 185:405-416.
  6. H. Jiang and W. H. Wong. 2009. Statistical inferences for isoform expression in RNA-Seq. Bioinformatics 25:1025-1032.
  7. J. Salzman et al. 2011. Statistical modeling of RNA-Seq data. Statistical Science 26:62-83.
  8. B. Li et al. 2010. RNA-Seq gene expression estimation with read mapping uncertainty. Bioinformatics 26: 493-500.
  9. B. Li and C. N. Dewey. 2011. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323.
  10. M. D. Robinson and A. Oshlack. 2010. A scaling normalization method for differential expression analysis of RNA-Seq data. Genome Biology 11:R25.
  11. T.J. Hardcastle and K. A. Kelly. 2010. baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics 11:422.
  12. S. Anders and W. Huber. 2010. Differential expression for sequence count data. Genome Biology 11:R106.
  13. J. H. Bullard et al. 2010. Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics 11:94.
  14. D. Witten. 2011. Classification and clustering of sequencing data using a Poisson model. Annals of Applied Statistics 5:2493-2518.
  15. O. Muralidharan et al. 2012. Detecting mutations in mixed sample sequencing data using empirical Bayes. Annals of Applied Statistics 6:1047-1067.
  16. G. I. Allen and Z. Liu. 2012. A log-linear graphical model for inferring genetic networks from high-throughput sequencing data. ArXiv 1204.3941.

All papers are available as PDF from the instructors.