Introduction to Bioconductor from Harvard

By: Harvard University
Duration: 5 Weeks

The structure, annotation, normalization, and interpretation of genome scale assays.

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Course ByInstructor
Harvard UniversityRafael Irizarry, Michael Love, Vincent Carey

Course Details

This free course from Harard will begin with an introduction to the relevant biology, explaining what we measure and why. Then we focus on the two main measurement technologies: next generation sequencing and microarrays. We then move on to describing how raw data and experimental information are imported into R and how we use Bioconductor classes to organize these data, whether generated locally, or harvested from public repositories or institutional archives.

Genomic features are generally identified using intervals in genomic coordinates, and highly efficient algorithms for computing with genomic intervals will be examined in detail. Statistical methods for testing gene-centric or pathway-centric hypotheses with genome-scale data are found in packages such as limma, some of these techniques will be illustrated in lectures and labs.

What you will learn?

  • What we measure with high-throughput technologies and why
  • Introduction to high-throughput technologies: Next generation sequencing and Microarrays
  • Preprocessing and normalization
  • The Bioconductor Genomic Ranges utilities
  • Genomic annotation

Other Details

Course Instructors

Rafael Irizarry: Professor of Biostatistics, T.H. Chan School of Public Health
Michael Love: Assistant Professor, Departments of Biostatistics and Genetics, UNC Gillings School of Global Public Health
Vincent Carey: Professor of Medicine (Biostatistics) in the Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School

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