Programme

Sunday, July 10

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

Monday, July 11

08:30–09:15 Lecture 01 Introduction to R and Bioconductor (MM)
09:15–10:00 Lecture 02 Hypothesis testing (WH)
10:00–10:30 Coffee break
10:30–11:15 Lecture 03 Learning to love the data frame (JB)
11:15–12:00 Lecture 04 Linear models (basic intro) (LW)
12:00–13:00 Lunch break (self-organised)
13:00–14:00 Installation help desk
14:00–15:30 Lab 1 Introduction to Bioconductor (MM)
15:30–17:00 Lab 2 Use of Git and GitHub with R, RStudio, and R Markdown (JB)
17:00–17:30 Flashlight talks

  • Amy Foulkes
  • David Watson
  • Daria Bunina
  • Gloria Gonzalez Curto

Tuesday, July 12

08:30–09:15 Lecture 05 Basics of sequence alignment and aligners (SAn)
09:15–10:00 Lecture 06 RNA-Seq data analysis and differential expression (ML)
10:00–10:30 Coffee break
10:30–11:15 Lecture 07 New workflows for RNA-seq (CS)
11:15–12:00 Lecture 08 Computing with sequences and genomic intervals (MM)
12:00–14:00 Lunch break (self-organised)
14:00–17:00 Lab 3 End-to-end RNA-Seq workflow (SA, ML and CS)
17:00–17:30 Flashlight talks

  • Eunice Carrasquinha
  • Tobias Zimmermann
  • Sarah Killcoyne
  • Andrea Mariossi

Wednesday, July 13

08:30–09:15 Lecture 09 Experimental design, batch effects and confounding (CS)
09:15–10:00 Lecture 10 Clustering and classification (VJC)
10:00–10:30 Coffee break
10:30–11:15 Lecture 11 Robust statistics (ML)
11:15–12:00 Lecture 12 Resampling: cross-validation, bootstrap and permutations (LW)
12:00–14:00 Lunch break (self-organised)
14:00–22:00 Social programme: excursion to the mountains, dinner

Thursday, July 14

08:30–09:15 Lecture 13 Multiple testing (WH)
09:15–10:00 Lecture 14 Working with annotation – genes, genomic features and variants (MM and VC)
10:00–10:30 Coffee break
10:30–11:15 Lecture 15 Analysis of microbiome data (marker gene based) (CS)
11:15–12:00 Lecture 16 Visualization, the grammar of graphics and ggplot2 (WH)
12:00–14:00 Lunch break (self-organised)
14:00–15:30 Lab 4 Reproducible research and R authoring with markdown and knitr (JB)
15:30–17:00 Lab 5 ChIP-Seq analysis basics (AR and MS)
17:00–17:30 Flashlight talks

  • Vivek Bhardwaj
  • Veronica E.H. Yoon
  • André Veríssmo
  • Husen Muhammad Umer
facultative Lab 6 Independent Hypothesis Weighting (WH)

Friday, July 15

08:30–09:15 Lecture 17 Gene set enrichment analysis (MM, ML)
09:15–10:00 Lecture 18 Meta-analysis (LW)
10:00–10:30 Coffee break
10:30–11:15 Lecture 19 Large data, performance, and parallelization; large-scale efficient computation with genomic intervals (MM, VJC)
11:15–12:00 Lecture 20 What should you do next? (JB)
12:00–14:00 Lunch break (self-organised)
14:00–17:00 Lab 7 Machine Learning, Parallelization and performance (WH, MM, VJC)
14:00–17:00 Lab 8 Graphics (WH)

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), Wolfgang Huber (WH), Michael Love (ML), Martin Morgan (MM), Alejandro Reyes (AR), Mike Smith (MS), Charlotte Soneson (CS), Levi Waldron (LW).