Analysis of RNA sequencing data with R/Bioconductor

Dates

November 01-12, 2021

Due to the COVID-19 outbreak, this course will be held online

 

overview

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 analyze genomic and transcriptomic  high-throughput data generated by next-generation sequencing, including:  hypothesis testing, data visualization, genomic region analysis, differential  expression analysis, and gene set analysis.

 

 

Preparation

Come to the first class with the following installed:

 

 

             R and Bioconductor: www.bioconductor.org/install

 

             R Studio: https://www.rstudio.com/products/rstudio/download3/

Textbook

 

             Modern Statistics for Modern Biology (by Holmes and Huber)

 

             The Bioconductor 2018 Workshop collection

 

program


** Session 1 – Introduction (Mon, Nov 01, 3-6 PM, Berlin time)

- Introduction to R / RStudio
- Creating high-quality graphics in R

 


** Session 2 – Hypothesis testing (Wed, Nov 03, 3-6 PM, Berlin time)

- CDF, p-value, binomial test
- types of error, t-test, permutation test



** Session 3 - Bioconductor (Fri, Nov 05, 3-6 PM, Berlin time)

- Introduction to Bioconductor
- Working with genomic region data in Bioconductor (GenomicRanges)


 
** Session 4 - RNA-seq data analysis (Mon, Nov 08, 3-6 PM, Berlin time)

- Characteristics of RNA-seq data
- Storing and analyzing RNA-seq data in Bioconductor (SummarizedExperiment)



** Session 5 - Differential expression analysis (Wed, Nov 03, 3-6 PM, Berlin time)

- Multiple hypothesis testing
- Performing differential expression analysis with DESeq2



** Session 6 - Gene set analysis (Fri, Nov 12, 3-6 PM, Berlin time)

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


Instructor

 

Dr. Ludwig Geistlinger

(Center for Computational Biomedicine, Harvard Medical School, USA)

 

Cost overview

Package 1

480 €


 

 

Cancellation Policy:

 

> 30  days before the start date = 30% cancellation fee

< 30 days before the start date= No Refund.

 

Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.