News:RNAseq data analysis with R/Bioconductor
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14 days ago
carlopecoraro2 ★ 2.3k

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.

Course Details:

  • Dates: October 30th to November 17th, 2023
  • Format: Online for global accessibility

Course website:

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.

Program Highlights:

  • 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.

R RNAseq Bioconductor • 118 views

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