News:Do you want to learn how to analyze your genomic data using R and Bioconductor?
Entering edit mode
4.4 years ago
carlopecoraro2 ★ 2.4k

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Dear all,

We still have a few places on our course " Genomics with R and Bioconductor"

Where: Free University (FU) Berlin (Germany)

When: 16-20 September 2019

Instructor: Dr. Ludwig Geistlinger - CUNY Graduate School of Public Health and Health Policy, New York (USA)


This course will provide biologists and bioinformaticians with practical statistical analysis skills to perform rigorous analysis of high-throughput genomic data. The course assumes basic familiarity with genomics and with R programming, but does not assume prior statistical training. It covers the statistical concepts necessary to design experiments and analyze high-throughput data generated by next-generation sequencing, including: exploratory data analysis, principal components analysis, clustering, differential expression, and gene set analysis.


Session 1 – Introduction

Monday - 09:30 to 17:30

Lecture 1: Data distributions

  • random variables
  • distributions
  • population and samples

Hands-On 1: Introduction to R

Lecture 2: Creating high-quality graphics in R

  • Visualizing data in 1D, 2D & more than two dimensions
  • Heatmaps
  • Data transformations

Hands-On 2: Graphics with base R and ggplot2

  • Session 2 – Hypothesis testing

Tuesday - 09:30 to 17:30

Lecture 1: Hypothesis testing theory

  • type I and II error and power
  • multiple hypothesis testing: false discovery rate, familywise error rate
  • exploratory data analysis (EDA)

Hands-On 1: Standard tests & EDA

Lecture 2: Hypothesis testing in practice

  • hypothesis tests for categorical variables (chi-square, Fisher's exact)
  • Monte Carlo simulation
  • Permutation tests

Hands-On 2: Permutation tests

  • Session 3 - Bioconductor

Wednesday – Classes from 09:30 to 17:30

Lecture 1: Introduction to Bioconductor

  • Incorporating Bioconductor in your data analysis
  • ExpressionSet / SummarizedExperiment
  • Annotation resources

Hands-On 1: Leveraging Bioconductor annotation resources

Lecture 2: Genomic intervals

  • Introduction to genomic region algebra
  • Basic operations: construction, intra- and inter-region operations
  • Finding overlaps

Hands-On 2: Solving common bioinformatic challenges with GenomicRanges

  • Session 4 - Next-generation sequencing data

Thursday - 09:30 to 17:30

Lecture 1: High-throughput count data

  • Characteristics of count data
  • Exploring count data
  • Modeling count data

Hands-On 1: Analyzing next-generation sequencing data

Lecture 2: Clustering and Principal Components Analysis

  • Measures of similarity
  • Hierarchical clustering
  • Dimension reduction
  • Principal components analysis (PCA)

Hands-On 2: Clustering & PCA

  • Session 5 - Differential expression and gene set analysis

Friday - 09:30 to 17:30

Lecture 1 - Differential expression analysis

  • Normalization
  • Experimental designs
  • Generalized linear models

Lab 1: Performing differential expression analysis with DESeq2

Lecture 2 - Gene set analysis

  • A primer on terminology, existing methods & statistical theory
  • GO/KEGG overrepresentation analysis
  • Functional class scoring & permutation testing
  • Network-based enrichment analysis

Lab 2: Performing gene set enrichment analysis with the EnrichmentBrowser

For the full list of our courses and Workshops, please see:

Should you have any questions, please feel free to contact us

Thanks and best regards,

Carlo Pecoraro, Ph.D
Physalia-courses DIRECTOR
Twitter: @physacourses
mobile: +49 17645230846!forum/physalia-courses

Genomics R Bioconductor • 872 views
Entering edit mode
4.3 years ago
carlopecoraro2 ★ 2.4k

Registration deadline has been extended to the 20th of August for our course Genomics with rstats and Bioconductor with Dr Ludwig Geistlinger (Levi Waldron lab) this September in Berlin.

If interested, please sign up here:


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