Programme

Lecture and lab topics

Biological domains

  • RNA-Seq from sequences to analysis: mapping, quantification at gene and transcript level
  • Single cell (droplet based) RNA-seq: exploratory analysis, quality assessment
  • Mass spectrometry-based proteomics and metabolomics
  • Image-based data and spatial omics (CODEX, MERFISH et al.)
  • Emerging topics and participant suggestions

Statistics and data science

  • Introduction to the Bioconductor project (community, infrastructure, data structures, annotation resources)
  • Visualization, including interactivity, PCA and other low-dimensional embeddings, clustering, distances, nearest-neighbour graphs
  • Statistical hypothesis testing, false discovery rate, multiple testing, filtering and weighting
  • Regression: experimental design and design matrices, power, identifiability, diagnostics, generalized linear models
  • Classification / supervised machine learning, multi-omic data integration methods
  • Data manipulation, EDA, and tidy data analysis, applied to high dimensional biological data
  • Reproducibility, best practices for computational research, method comparison, benchmarking
  • Emerging topics and participant suggestions

Schedule (subject to change)

Date/Time Content
Sun 23 June
18:00-20:00 Registration & help desk
18:00-20:00 Get together with drinks
Mon 24 June
08:30-09:15 Lecture: Introduction to Bioconductor (Vince Carey)
09:15-10:00 Lecture: PCA and other low-dimensional embeddings (Robert Gentleman)
10:00-10:30 ~~~ Coffee ~~~
10:30-11:15 Lecture: Regression: power, identifiability, diagnostics (Michael Love)
11:15-12:00 Lecture: Statistical testing and multiple hypotheses (Wolfgang Huber)
12:00-14:00 ~~~ Lunch break ~~~
14:00-17:00 Lab: R and Bioconductor basics
17:00-17:30 Flashlight talks
20:10-22:00 Evening session: Drinks will be provided
20:30-21:30 Group work: Creation of week-long project groups, choice of projects
Tue 25 June
08:30-09:15 Lecture: RNA-seq intro: biology of transcription, quantification,
batch effects and QC (Michael Love)
09:15-10:00 Lecture: 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: Single-cell RNA-seq: exploration, quality control,
low-dimensional embeddings (Davide Risso)
11:15-12:00 Lecture: Distances, nearest-neighbour graphs and clustering (Vincent Carey)
12:00-14:00 ~~~ Lunch break ~~~
14:00-17:00 Lab: End-to-end RNA-Seq workflow
14:00-17:00 Lab: Single-cell transcriptomics
17:00-17:30 Flashlight talks
20:10-22:00 Evening session: Drinks will be provided
20:30-21:30 Group work: Continuation of projects from Monday night
Wed 26 June
08:30-09:15 Lecture: Bioconductor advanced topics: annotation resources (Vince Carey)
09:15-10:00 Lecture: Single cell RNA-seq advanced topics: pseudo-bulking,
double-dipping (Charlotte Soneson)
10:00-10:30 ~~~ Coffee ~~~
10:30-11:15 Lecture: Multi-condition single cell RNA-seq differential analysis
(or when is the right time to categorize?) (Wolfgang Huber)
11:15-12:00 Lecture: Single cell advanced topics: trajectories,
multi-omics (Charlotte Soneson, Davide Risso)
12:00-14:00 ~~~ Lunch break ~~~
14:00-17:00 Social Programme: Excursion to the mountains and dinner
Thu 27 June
08:30-09:15 Lecture: Mass spectrometry-based proteomics
including single-cell (Laurent Gatto)
09:15-10:00 Lecture: Mass spectrometry-based metabolomics (Laurent Gatto)
10:00-10:30 ~~~ Coffee ~~~
10:30-12:00 Lab: Proteomics/metabolomics (Laurent Gatto and Philippine Louail)
12:00-14:00 ~~~ Lunch break ~~~
14:00-14:45 Lecture: Spatial (transcript)omics (Davide Risso)
14:45-15:15 Lecture:: R programming and debugging (Laurent Gatto)
15:30-17:00 Lab: Intro to Tidyomics: tidy data analysis applied to omics data
15:30-17:00 Lab: Multi-condition single cell RNA-seq differential analysis
17:00-17:30 Flashlight talks
20:10-22:00 Evening session: Drinks will be provided
20:30-21:30 Group work: Finalizing group work for presentations Friday afternoon
Fri 28 June
08:30-09:15 Lecture: Design of High Throughput Experiments and their Analysis (Charlotte Soneson)
09:15-10:00 Lecture: Machine learning (Robert Gentleman)
10:00-10:30 ~~~ Coffee ~~~
10:30-11:15 Lecture: The multiplicity of possible analysis strategies (and how to handle it) in omics applications (Anne-Laure Boulesteix)
11:15-12:00 Lecture: The multiplicity of possible analysis strategies (and how to handle it) in benchmark studies (Anne-Laure Boulesteix)
12:00-14:00 ~~~ Lunch break ~~~
14:00-17:00 Group project presentations
17:00 Closing remarks

Lecturers and Teaching Assistants

Anne-Laure Boulesteix (ALB) Vince Carey (VJC) Maria Doyle (MD) Laurent Gatto (LG) Robert Gentleman (RG) Wolfgang Huber (WH) Philippine Louail (PL) Michael Love (ML) Davide Risso (DR) Charlotte Soneson (CS) Ilaria Billato (IB)