Computational Statistics for Genome Biology (CSAMA)

Brixen-Bressanone, Italy

2014-06-22 ~ 2013-06-28

Instructors

Description

This one-week intensive course teaches current approaches in the statistical and computational analysis of large-scale experiments in biology. The course focuses on the methods for downstream analyses of high-throughput sequencing experiments including RNA sequencing (differential expression), DNA sequencing (variant calling), ChIP-Seq. Lectures also cover essentials including statistical testing, linear models, machine learning, visualisation and bioinformatic annotation. Emphasis is given to practical problem solving skills using open-source software from the Bioconductor, CRAN and other projects. The course is intended for researchers who have basic familiarity with the experimental technologies and the biology of the genome, and who are interested in developing their own, advanced data analyses using a scripting environment. The four practical sessions of the course will require simple script understanding in the computer language R. A tutorial on the required more advanced features of R will be provided, students are advised to familiarize themselves with the very basics of R beforehand. (Consider one of the many online resources or books, e.g. R-Intro from the R Project, Germán Rodríguez, R-Studio.

Materials

Monday, June 22

Morning talks

Afternoon labs

Tuesday

Morning talks

Afternoon labs

Wednesday

Morning talks

Afternoon labs

Thursday

Morning talks

Afternoon labs

Friday

Morning talks

Afternoon labs

Bioconductor Release »

Packages in the stable, semi-annual release:


Bioconductor is also available as an Amazon Machine Image.
Fred Hutchinson Cancer Research Center