Dear all,
there are the last 3 seats available for the 3rd edition of the Analysis of RNA sequencing data with R/Bioconductor course.
Dates: online, November 7th-18th
This course will provide biologists and bioinformaticians with practical statistical skills to perform rigorous analysis of high-throughput genomic data. The course assumes basic familiarity with genomics and 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.
** Session 1 – Introduction (Mon, Nov 07, 3-6 PM, Berlin time)
- Introduction to R / RStudio
- Creating high-quality graphics in R
** Session 2 – Hypothesis testing (Wed, Nov 09, 3-6 PM, Berlin time)
- CDF, p-value, binomial test
- types of error, t-test, permutation test
** Session 3 - Bioconductor (Fri, Nov 11, 3-6 PM, Berlin time)
- Introduction to Bioconductor
- Working with genomic region data in Bioconductor (GenomicRanges)
** Session 4 - RNA-seq data analysis (Mon, Nov 14, 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 16, 3-6 PM, Berlin time)
- Multiple hypothesis testing
- Performing differential expression analysis with DESeq2
** Session 6 - Gene set analysis (Fri, Nov 18, 3-6 PM, Berlin time)
- A primer on terminology, existing methods & statistical theory
- GO/KEGG overrepresentation analysis
- Functional class scoring & permutation testing
Full list of our Courses and Workshops: https://www.physalia-courses.org/courses-workshops
