Skip to content

Latest commit

 

History

History
42 lines (32 loc) · 2.11 KB

README.md

File metadata and controls

42 lines (32 loc) · 2.11 KB

R and Bioconductor for Genomic Analysis

Date: Monday and Tuesday, September 11 - 12
Instructors: Martin Morgan, Ezgi Karaesmen, Abbas Rizvi
Affiliation: Roswell Park Cancer Institute; Ohio State University
Contact: Martin.Morgan at RoswellPark.org

This two-day workshop provides an introduction to R and Bioconductor for the analysis and comprehension of high-throughput genomic data. The workshop assumes modest knowledge of R. We will move at a steady pace, and cover quite a bit of ground. The goals are to familiarize particpants with common ways in which data, including genomic data, are explored and analyzed in R, and to provide participants with tools necessary for their own continued self-education.

Day 1

  • Basics of R -- vectors, data.frames, linear models
  • Tidy data
  • Bioconductor data representations -- GenomicRanges, SummarizedExperiment, and friends
  • Organizing work -- scripts, markdown, packages

Day 2

  • Exploring RNA-seq data
  • Differential expression analysis with DESeq2
  • Results in context -- annotation, gene set enrichment, etc.
  • Writing better R code

Recent courses:

  • Moffitt-2017 -- 2 day introduction to R and Bioconductor
  • UP-STAT-2017 -- 1 two-hour session on exploring high-throughput data.
  • R-CDSE-Days-2017 -- 1 three-hour session on high-throughput genomic analysis in R and Bioconductor.
  • RIntro.RPCI.Jan2017 -- 5 one-hour sessions introduction R to the Roswell Park community.
  • Technion.2016 -- 3 three-hour sessions introducing Bioconductor (and R).

Bioconductor Course Archive