Dear all, We are thrilled to announce our upcoming course on "Analysis of RNA Sequencing Data with R/Bioconductor", designed to empower biologists and bioinformaticians with the essential skills needed for robust high-throughput genomic data analysis.
- Dates: October 30th to November 17th, 2023
- Format: Online for global accessibility
Course website: https://www.physalia-courses.org/courses-workshops/course19/
Instructors: Dr Ludwig Geistlinger (Harvard Medical School, USA) and Dr. Michael Love (UNC-Chapel Hill, USA)
Course Overview: This comprehensive course assumes basic familiarity with genomics and R programming, making it accessible to a wide audience. It covers critical statistical concepts necessary for the analysis of high-throughput genomic and transcriptomic data generated by next-generation sequencing. Topics include hypothesis testing, data visualization, genomic region analysis, differential expression analysis, and gene set analysis.
- Session 1 (Oct 30): Introduction to R/RStudio and high-quality graphics creation.
- Session 2 (Nov 01): Hypothesis testing, CDF, p-value, t-test, and more.
- Session 3 (Nov 3): Tidyverse introduction, tidy analysis paradigms, and integration with ggplot2.
- Session 4 (Nov 6): Introduction to Bioconductor and working with genomic region data.
- Session 5 (Nov 8): RNA-seq data characteristics and analysis using Bioconductor.
- Session 6 (Nov 10): Genomic data visualization using Gviz and ComplexHeatmap.
- Session 7 (Nov 13): Multiple hypothesis testing and DESeq2 for differential expression analysis.
- Session 8 (Nov 15): Gene set analysis, GO/KEGG overrepresentation, and functional class scoring.
- Session 9 (Nov 17): Bioconductor tidy workflows for genomic and transcriptomic data.
Should you have any questions or require additional information, please do not hesitate to contact us.