Daily schedule

The programme is supposed to roughly follow this schedule.

  1. Monday Brief overview of molecular data. Introduction to statistical methods for high-dimensional data, linear models and regularization methods (Claus Ekstrøm)
    • Introduction
    • Big-p small-n problems
    • Multiple testing techniques (inference correction, false discovery rates, q-values)
    • The correlation vs. causation and prediction vs. hypothesis differences
    • Generalized linear models refresher
    • Principal component regression, and principal component regression
    • Penalized regression
  2. Tuesday Network biology (Lars Juhl Jensen)
    • Software to install Cytoscape
    • Quality assessment and heterogeneous data integration
    • Biomedical text mining (named entity recognition & co-occurrence analysis)
    • Network analysis with STRING and Cytoscape
  3. Wednesday Genome-wide association studies (Claus Ekstrøm)
    • GWAS
    • Imputation
    • Common variants vs rare variants. Sequence Kernel Association Test
    • Enrichment approaches, gene-set analyses
  4. Thursday Analysis of array data and integrative data analysis (Claus Ekstrøm)
    • Zero-inflated and hurdle models (microbiome data and RNA-seq revisited)
    • Gene expression analyses
    • Matrix factorization
    • Combining data from multiple platforms and experiments
    • Inference methods for combined (and simultaneous) data
    • DNA variant calling
  5. Friday Analysis of RNA sequencing data (Stefan Seemann)
    • Alignment methods
    • Dynamic programming of pairwise alignment
    • Read mapping and assembly
    • Expression analysis

Claus Ekstrøm 2023