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CSAMA 2016: Statistical Data Analysis for Genome-Scale Biology

July 10-15, 2016
Bressanone-Brixen, Italy
URL: http://www.huber.embl.de/csama2016/

Lecturers: Simon Anders, Institute for Molecular Medicine, Helsinki; Jennifer Bryan, University of British Columbia, Vancouver; Vincent J. Carey, Channing Laboratory, Harvard Medical School; Wolfgang Huber, European Molecular Biology Laboratory (EMBL), Heidelberg; Michael Love, Dana Farber Cancer Institute and the Harvard School of Public Health; Martin Morgan, Roswell Park Cancer Institute, Buffalo, New York; Charlotte Soneson, University of Zurich; Levi Waldron, CUNY School of Public Health at Hunter College, New York.

Teaching Assistants: Simone Bell, EMBL, Heidelberg; Alejandro Reyes, EMBL, Heidelberg; Mike L. Smith, EMBL, Heidelberg.

Resources

Monday, July 11

Lectures

  • 01 Introduction to R and Bioconductor (MM) pdf
  • 02 Hypothesis testing (WH) pdf
  • 03 Learning to love the data frame (JB) pdf
  • 04 Linear models (basic intro) (LW) pdf

Labs

  • 1 Introduction to R and Bioconductor (MM) html
  • 2 Use of Git and GitHub with R, RStudio, and R Markdown (JB) pdf

Tuesday, July 12

Lectures

  • 05 Basics of sequence alignment and aligners (SAn) pdf
  • 06 RNA-Seq data analysis and differential expression (ML) pdf
  • 07 New workflows for RNA-seq (CS) pdf
  • 08 Computing with sequences and genomic intervals (MM) pdf

Labs

  • 3 End-to-end RNA-Seq workflow (SA, ML and CS) Rmd

Wednesday, July 13

Lectures

  • 09 Experimental design, batch effects and confounding (CS) pdf
  • 10 Clustering and classification (VJC) pdf
  • 11 Robust statistics (ML) pdf
  • 12 Resampling: cross-validation, bootstrap and permutations (LW) pdf

Thursday, July 14

Lectures

  • 13 Multiple testing (WH) pdf
  • 14 Working with annotation – genes, genomic features and variants (MM and VC) pdf
  • 15 Analysis of microbiome data (marker gene based) (CS) pdf
  • 16 Visualization, the grammar of graphics and ggplot2 (WH) pdf

Labs

  • 4 Reproducible research and R authoring with markdown and knitr (JB) github
  • 5 ChIP-Seq analysis basics (AR and MS) Rmd html Rpackage

Friday, July 15

Lectures

  • 17 Gene set enrichment analysis (MM, ML) pdf; pdf
  • 18 Meta-analysis (LW) pdf
  • 19 Large data, performance, and parallelization; large-scale efficient computation with genomic intervals (MM, VJC) pdf; pdf
  • 20 What should you do next? (JB) pdf

Labs

  • 6 Machine Learning, Parallelization and performance (WH, MM, VJC) Independent Hypthesis weighting Rmd html; Efficient and Parallel html; Machine Learning html Rmd pdf Code
  • 7 Graphics (WH) Rmd