Advanced Bioconductor
offered by Harvard University

Private University
3 Campuses
Estd. 1636

Advanced Bioconductor
at
Harvard University
Overview

Learn advanced approaches to genomic visualization, reproducible analysis, data architecture, and exploration of cloud-scale consortium-generated genomic data.

Duration	5 weeks
Mode of learning	Online
Difficulty level	Intermediate
Official Website	Go to Website
Course Level	UG Certificate

Advanced Bioconductor
at
Harvard University
Highlights

Earn a certificate of completion

Advanced Bioconductor
at
Harvard University
Course details

Skills you will learn

R Statistics Data visualization Data analysis Data Science

What are the course deliverables?

Static and interactive visualization of genomic data
Reproducible analysis methods
Memory-sparing representations of genomic assays
Working with multiomic experiments in cancer
Targeted interrogation of cloud-scale genomic archives

More about this course

In this course, we begin with approaches to visualization of genome-scale data, and provide tools to build interactive graphical interfaces to speed discovery and interpretation. Using knitr and rmarkdown as basic authoring tools, the concept of reproducible research is developed, and the concept of an executable document is presented. In this framework reports are linked tightly to the underlying data and code, enhancing reproducibility and extensibility of completed analyses. We study out-of-memory approaches to the analysis of very large data resources, using relational databases or HDF5 as "back ends" with familiar R interfaces. Multiomic data integration is illustrated using a curated version of The Cancer Genome Atlas. Finally, we explore cloud-resident resources developed for the Encyclopedia of DNA Elements (the ENCODE project). These address transcription factor binding, ATAC-seq, and RNA-seq with CRISPR interference.
Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.

Advanced Bioconductor
at
Harvard University
Curriculum

Data Science, Data Analysis, Data Visualization, R, Statistics, Biology

Advanced Bioconductor
at
Harvard University
Faculty details

Rafael Irizarry

Designation : Professor of Biostatistics, T.H. Chan School of Public Health

Michael Love

Designation : Assistant Professor, Departments of Biostatistics and Genetics, UNC Gillings School of Global Public Health

Vincent Carey

Designation : Professor of Medicine (Biostatistics) in the Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School