Programme

Lecture and Lab topics

  • RNA-Seq from raw data to DESeq2: mapping, quantification at gene and transcript level, gamma-Poisson model, DESeq2
  • Single cell (droplet based) RNA-seq: exploratory analysis, quality assessment, dimension reduction (incl., t-SNE, UMAP)
  • Visualisation / graphics, PCA and other low-dimensional embeddings, Clustering, distances, nearest-neighbour graphs (with sc-RNA-Seq examples)
  • Statistical hypothesis testing, false discovery rate, multiple testing, filtering and weighting
  • Regression: more on design matrices, power, identifiability, diagnostics, generalized linear models for count data
  • Classification / supervised machine learning
  • Image-based data and Spatial omics (CODEX, MERFISH et al.)
  • Introduction to the Bioconductor project (community, organisational structure, website, important infrastructure packages, data structures, annotation resources)
  • Immunobioinformatics
  • Mass spectrometry-based proteomics and metabolomics
  • Emerging topics and participant suggestions

Sunday, 11 June

18:00–20:00 Registration & Installation help desk
18:00–20:00 Get Together with drinks and nibbles
Please see here for the teaching material - lectures and labs.

Monday, 12 June

08:30–09:15 Lecture 01 Introduction to Bioconductor (Lori Kern)
09:15–10:00 Lecture 02 PCA and other low-dimensional embeddings (Robert Gentleman)
10:00–10:30 Coffee
10:30–11:15 Lecture 03 Statistical tests (Wolfgang Huber)
11:15–12:00 Lecture 04 Design of High Throughput Experiments and their Analysis (Charlotte Soneson)
12:00–14:00 Lunch break (Self sourced in Brixen)
13:30–14:00   Installation help desk
14:00–17:00 Lab R and Bioconductor Basics
17:00–17:30 Flashlight talks
  • Julia Philipp
  • Sara Lobato Moreno
  • Jamie Yam Auxillos
  • Caroline Lohoff
  • Dawn Shuiping Lin
Each talk 5 min + 2 min questions
20:10–22:00 Evening session Drinks will be provided
20:30–21:15 Group work | Demos
  • Group projects (Vincent Carey, Robert Gentleman)
  • Interactive exploration and data quality assessment for matrix-shaped data with iSEE (Charlotte Soneson)
  • Tidy analysis of genomic data with plyranges, and tidy ranges tutorial (Michael Love)
  • HDF5 / large single-cell datasets (Davide Risso)
21:15–22:00 Follow-up discussions on the lawn

Tuesday, 13 June

08:30–09:15 Lecture 05 RNA-Seq intro: biology of transcription, quantification, batch effects and QC (Michael Love)
09:15–10:00 Lecture 06 RNA-Seq for DE: Types of DE, modeling counts, scaling, transcript lengths, parameter estimation (Charlotte Soneson)
10:00–10:30 Coffee
10:30–11:15 Lecture 07 Single-cell RNA-seq: exploration, quality control, low-dimensional embeddings (Davide Risso)
11:15–12:00 Lecture 08 Distances, nearest-neighbour graphs and clustering (Vincent Carey)
12:00–14:00 Lunch break (Self sourced in Brixen)
14:00–17:00 Lab 3 End-to-end RNA-Seq workflow (Michael Love and Charlotte Soneson)
14:00–17:00 Lab 4 Single-cell transcriptomics (Davide Risso)
17:00–17:30 Flashlight talks
  • Giulia Graziano
  • Karin Prummel
  • James Bryson
  • Alina Batzilla
Each talk 5 min + 2 min questions
20:10–22:00 Evening session Drinks will be provided
20:30–21:15 Demos / tutorials
  • What you need to know for submitting a package to Bioconductor (Lori Kern)
  • Reproducible research and open science (Laurent Gatto, Charlotte Soneson)
  • Shiny (Vincent Carey)
21:15–22:00 Follow-up discussions on the lawn

Wednesday, 14 June

08:30–09:15 Lecture 09 Human Cell Atlas |> Ontologies |> Shiny %<>% Bioconductor (Vincent Carey)
09:15–10:00 Lecture 10 Spatial (transcript)omics (Davide Risso)
10:00–10:30 Coffee
10:30–11:15 Lecture 11 Advanced transcriptomic inference: bootstrapping (transcript-level inferential uncertainty), pseudo-bulking, double-dipping (Michael Love and Charlotte Soneson)
11:15–12:00 Lecture 12 Bioconductor Annotation Resources | Caching (Lori Kern)
12:00–14:00 Lunch break (Self sourced in Brixen)
14:00–22:30 Social programme Excursion to the mountains and dinner

Thursday, 15 June

08:30–09:15 Lecture 13 Mass spectrometry-based proteomics, incl. single-cell (Laurent Gatto)
09:15–10:00 Lecture 14 Mass spectrometry-based metabolomics (Johannes Rainer)
10:00–10:30 Coffee
10:30–11:30 Lecture 15 Regression (Sarah Kaspar)
11:30–12:00 Lecture 16 Visualization (Wolfgang Huber)
12:00–14:00 Lunch break (Self sourced in Brixen)
14:00–17:00 Lab 5 Proteomics/metabolomics (Laurent Gatto, Johannes Rainer)
14:00–17:00 Lab 6 Working with image data (Wolfgang Huber)
14:00–17:00 Lab 7 Tidy genomic analysis workflows (Michael Love)
14:00–17:00 Lab 9 Annotation of untargeted metabolomics data (Johannes Rainer)
17:00–17:30 Flashlight talks
  • Felina Lenkeit
  • Anna Diamant
  • Mathilde Moens
  • Gaël Hammer

Friday, 16 June

08:30–09:15 Lecture 17 Machine learning (Robert Gentleman)
09:15–10:00 Lecture 18 Immunoinformatics (Katharina Imkeller)
10:00–10:30 Coffee
10:30–11:15 Lecture 19 Advanced single cell omics II: Trajectories, pseudo-time, bifurcations, spatial statistics (Charlotte | Davide | Wolfgang)
11:15–12:00 Lecture 20 Group projects (Robert Gentleman, Vincent Carey)
12:00–14:00 Lunch break
14:00–16:30 Lab 5 Proteomics/metabolomics (Laurent Gatto, Johannes Rainer)
14:00–16:30 Lab 6 Working with image data (Wolfgang Huber)
14:00–16:30 Lab 9 Annotation of untargeted metabolomics data (Johannes Rainer)
16:30-17:00 Q&A Career panel (open questions for instructors)
17:00   Closing remarks

Lecturers and Teaching Assistants

Vince Carey (VJC) Laurent Gatto (LG) Robert Gentleman (RG) Wolfgang Huber (WH) Katharina Imkeller (KI) Sarah Kaspar (SK) Lori Kern (LK) Mike Love (ML) Julia Philipp (JP) Johannes Rainer (JR) Davide Risso (DR) Charlotte Soneson (CS) Simone Bell (SB)