SFB 1243 Cancer Evolution

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Workshop: NGS Data Analysis, planned for November 7-11, 2016!

Dr. Ines Hellmann, Dr. Sebastian Bultmann, Dr. Andreas Wollstein, BMC in Martinsried

07.11.2016 – 11.11.2016

This course offers valuable starting skills for those IRTG members who will be analyzing seq data for their projects.

This one-week course will include the basics on NGS analysis, a lot of R as well as RNA seq methods.

Time: November 7-11, 2016 from 9:00-17:00

Location: Biomedical Center Munich (BMC), room N01.012

Please bring your own laptop (any difficulties? contact Elizabeth). Previous knowledge is helpful but not required.

Open for all IRTG 1243 members!

Sign up with Elizabeth irtg1243@bio.lmu.de

Preliminary Syllabus:

Statistical analysis of RNA-Seq data

The focus will be on the part of analysis after a count-table was generated. A lot of general statistics will be repeated in the process, while linking these statistics to their implementations in various commonly used Bioconductor packages.

Day 1 Sanity checking the data:
Normalization (size-factors & mean-variance relationships, clustering methods (PCA, t-SNE, k-means, hierarchical clustering)

Day 2 Linear Regression (and its implementations in limma)

Day 3 Generalized linear models
(Negative binomial as in DESeq, Shrinkage factors or information borrowing across genes, Multiple testing correction)

Day 4 Models for Single Cell Analysis
(Dropout- rate: modeling & normalization MAST & scone)

Day 5 NGS Pipelines and Programs & Interpreting the QC of data
— when to use which mapper, programs for file-format conversion ...

With this set-up, plain R will be used for the first 4 days, and on the last day a short introduction to the server will be given as well as an introduction to the pipelines that will be implemented on the server.

In comparison to Ines' Master Bio class, the focus on the statistics will be stronger, and the addition of single cell analysis is new.
If you have any questions about eligibility (previous knowledge) or the scope of the course, please contact Elizabeth (see above) or Ines Hellmann hellmann@biologie.uni-muenchen.de.