CSAMA'22
Statistics and Computing in Genome Scale Biology

All teaching materials can be found on the CSAMA Github repo.

Friday (Day5)

Lecture slides

Linear Model Design - Robert Gentleman
Design of analysis - Wolfgang Huber
Immunoinformatics - Katharina Imkeller

Thursday (Day4)

Lecture slides

Mass spectrometry-based proteomics - Laurent Gatto
Visualization - Wolfgang Huber
Supervised machine learning - Robert Gentleman
Mass spectrometry-based metabolomics - Johannes Rainer

Lab materials

Proteomics - Laurent Gatto and Johannes Rainer
Basic Testing - Wolfgang Huber
Multiple Testing and Independent Hypothesis Weighting - Wolfgang Huber
Multi Assay Experiment - Levi Waldron
Lab9 - Annotation of untargeted metabolomics data - Johannes Rainer

Wednesday (Day3)

Lecture slides

Human Cell Atlas | Ontologies | Shiny - Vincent Carey
Statistical tests II - Wolfgang Huber
Annotation Resources - Johannes Rainer

Group Project

Tuesday (Day2)

Lecture slides

Basics of RNA-Seq - Davide Risso
Regression II - Charlotte Soneson
Single-cell RNA-seq: data properties, embeddings - Davide Risso
Distances, nearest-neighbour graphs and clustering - Vincent Carey

Lab materials

End-to-end RNA-Seq workflow - Charlotte Soneson
Single-cell transcriptomics - Davide Risso

Evening Session

Open and reproducible research - Laurent Gatto & Charlotte Soneson
Introduction to Cloud and GPU Computing - Martin Morgan and Nitesh Turaga

Monday (Day1)

Lecture slides

Introduction to Bioconductor - Martin Morgan
PCA and other low-dimensional embeddings - Levi Waldron
Statistical tests I - Wolfgang Huber
Regression I - Robert Gentleman

Lab materials

Lab 1 - R and Bioconductor Basics - Martin Morgan

Evening session

Isee Overview - Charlotte Soneson
Isee Slides - Charlotte Soneson
Introduction to Docker - Nitesh Turaga