Harvard University is offering free online course on Introduction to Bioconductor: Annotation and Analysis of Genomes and Genomic Assays. The structure, annotation, normalization, and interpretation of genome scale assays.
Course At A Glance
Length: 4 weeks
Effort: 2-4 hours pw
Subject: Biology & Life Sciences
Institution: Harvard University and edx
Certificate Available: Yes, Add a Verified Certificate for $49
Session: Course Starts on May 30, 2018
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About This Course
We begin with an introduction to the 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.
Why Take This Course?
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.
- Introduction to high-throughput technologies
Next Generation Sequencing
- What we measure with high-throughput technologies and why
- Preprocessing and Normalization
- The Bioconductor Genomic Ranges Utilities
- Genomic Annotation
Rafael Irizarry is a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and a Professor of Biostatistics and Computational Biology at the Dana Farber Cancer Institute.
Michael Love is a postdoctoral fellow with Dr. Irizarry in the Department of Biostatistics at the Dana Farber Cancer Institute and Harvard T.H. Chan School of Public Health.
Vincent Carey is Associate Professor of Medicine (Biostatistics) in the Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School.
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