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Statistics & Bioinformatics: Introduction & Application


Franz Klein


Modern research largely depends on the analysis and evaluation of large and complex datasets. While many researchers evaluate their data in cooperation with experts in the field of statistics or bioinformatics, it is still vital to be able to judge one’s own data in order to properly plan and set up experiments. In addition, also smaller datasets, created in the lab every day, need to be statistically evaluated to ensure correct interpretation.


This workshop aims at providing students with basic knowledge about statistical methods and available software in order to enable them to accurately analyze and precisely classify their data.



Introductory lectures will be combined with several hands-on sessions.

  • Exploratory data analysis
  • Introduction to the “R” software
  • Introduction to available statistical tests
  • Linear regression
  • ANOVA analysis
  • NGS data and de novo genome assembly
  • Genome annotation and browsing
  • Comparative assembly and variant calling
  • Transcriptomics, RNAseq, transcript assembly
  • Mapping, quantitation, differential expression and clustering
  • Multiple sequence alignment, phylogenetic analysis
  • Primer design, introgression analysis


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