Dear all,
Registrations are open for the 5th edition of the online course on the Analysis of RNAseq data with R/Bioconductor: https://www.physalia-courses.org/courses-workshops/course19/
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.
The course takes place over 6 days, with each session lasting 3 hours:
Session 1 – Introduction (Nov 4, 12-3 PM, Berlin time)
- Introduction to R / RStudio
- Creating high-quality graphics in R
Session 2 – Hypothesis testing (Nov 6, 12-3 PM, Berlin time)
- CDF, p-value, binomial test
- types of error, t-test, permutation test
Session 3 - Introduction to Bioconductor (Nov 8, 12-3 PM, Berlin time)
- Introduction to Bioconductor
- Working with genomic region data in Bioconductor (GenomicRanges)
Session 4 - RNA-seq data analysis (Nov 11, 12-3 PM, Berlin time)
- Characteristics of RNA-seq data
- Storing and analyzing RNA-seq data in Bioconductor (SummarizedExperiment)
Session 5 - Differential expression analysis (Mon, Nov 13, 12-3 PM, Berlin time)
- Multiple hypothesis testing
- Performing differential expression analysis with DESeq2
Session 6 - Gene set analysis (Wed, Nov 15, 12-3 PM, Berlin time)
- A primer on terminology, existing methods & statistical theory
- GO/KEGG overrepresentation analysis
- Functional class scoring & permutation testing
