Programme

Sunday, June 11

17:00–18:00 Registration & Installation help desk
18:00–20:00 Get Together with drinks and nibbles

Monday, June 12

08:30–09:15 Lecture 01 Introduction to R and Bioconductor (MM)
09:15–10:00 Lecture 02 Computing with Sequences and Ranges (MM)
10:00–10:30 Coffee break
10:30–11:15 Lecture 03 Tabular data management (JB)
11:15–12:00 Lecture 04 Annotation resources (JR with MM)
12:00–13:00 Lunch break
13:00–13:30 Installation help desk
13:30–15:00 Lab 1 Introduction to Bioc (MM)
15:00–16:30 Lab 2
16:30–17:00 Flashlight talks

Tuesday, June 13

08:30–09:15 Lecture 05 Basics of sequence alignment and aligners (SA)
09:15–10:00 Lecture 06 RNA-Seq data analysis and differential expression (SA)
10:00–10:30 Coffee break
10:30–11:15 Lecture 07 New workflows for RNA-seq (CS)
11:15–12:00 Lecture 08 Hypothesis testing (WH)
12:00–13:30 Lunch break
13:30–16:30 Lab 3 End-to-end RNA-Seq workflow (SA and CS)
Optional: Independent hypothesis weighting (WH)
16:30–17:00 Flashlight talks

Wednesday, June 14

08:30–09:15 Lecture 09 Multiple testing (WH)
09:15–10:00 Lecture 10 Linear models (basic intro) (LW)
10:00–10:30 Coffee break
10:30–11:15 Lecture 11 Experimental design, batch effects and confounding (CS)
11:15–12:00 Lecture 12 Robust statistics: median, MAD, rank test, Spearman, robust linear model (VJC)
12:00–13:30 Lunch break
13:30–22:00 Social programme: excursion to the mountains, dinner

Thursday, June 15

08:30–09:00 Lecture 13 Visualization, the grammar of graphics and ggplot2 (WH)
09:00–09:45 Lecture 14 Mass spec proteomics & metabolomics (LG and JR)
09:45–10:15 Coffee break
10:15–11:00 Lecture 15 Clustering and classification (VJC)
11:00–11:30 Lecture 16 Resampling: cross-validation, bootstrap, and permutation tests (LW)
11:30–12:00 Lecture 17 Analysis of microbiome marker gene data (CS)
12:00–13:30 Lunch break
13:30–15:00 Lab 4 Mass spec proteomics & metabolomics (LG and JR)
15:00–16:30 Lab 5 MultiAssayExperiment (LW)
16:30–17:00 Flashlight talks

Friday, June 16

08:30–09:15 Lecture 18 Gene set enrichment analysis (MM)
09:15–10:00 Lecture 19 Working with large-scale data (MM with VJC)
10:00–10:30 Coffee break
10:30–11:15 Lecture 20 Developer Practices, Part I (JB)
11:15–12:00 Lecture 21 Developer Practices, Part II (JB)
12:00–13:30 Lunch break
13:30–16:30 Lab 7 Graphics (WH)
13:30–16:30 Lab 8 Machine learning (supervised) (WH)
13:30–16:30 Lab 8 Large data, performance, and parallelization; large-scale efficient computation with genomic intervals (VJC, MM)

Flashlight talks

Each talk 5 min + 2 min questions

Lecturers and Teaching Assistants

Simon Anders (SA), Simone Bell (SB), Jennifer Bryan (JB), Vincent J. Carey (VJC), Laurent Gatto (LG), Wolfgang Huber (WH), Martin Morgan (MM),  Mike Smith (MS), Johannes Rainer (JR), Charlotte Soneson (CS), Levi Waldron (LW).