Learn to use tools from the Bioconductor project to perform analysis of genomic data. This is the fifth course in the Genomic Big Data Specialization from Johns Hopkins University.
Bioconductor for Genomic Data Science
Bioconductor for Genomic Data Science
This course is part of Genomic Data Science Specialization
Instructor: Kasper Daniel Hansen, PhD
Access provided by New York State Department of Labor
24,297 already enrolled
Gain insight into a topic and learn the fundamentals.
3.8
(381 reviews)
8 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
87%
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Assessments
4 assignments
Taught in English
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This course is part of the Genomic Data Science Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
The class will cover how to install and use Bioconductor software. We will discuss common data structures, including ExpressionSets, SummarizedExperiment and GRanges used across several types of analyses.
What's included
16 videos3 readings1 assignment
In this week we will learn how to represent and compute on biological sequences, both at the whole-genome level and at the level of millions of short reads.
What's included
8 videos1 assignment
In this week we will cover Basic Data Types, ExpressionSet, biomaRt, and R S4.
What's included
9 videos1 assignment
In this week, we will cover Getting data in Bioconductor, Rsamtools, oligo, limma, and minfi
What's included
7 videos1 reading1 assignment
Instructor
Instructor ratings
3.8 (37 ratings)Offered by
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3.8
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Showing 3 of 381
MA
5
Reviewed on Mar 12, 2016
Excellent introduction to Bioconductor. Thanks to the team. However, absence of inputs from TA or Instructor was felt in the discussion.
SS
4
Reviewed on Sep 4, 2016
A nice course to introduce Bioconductor to students
GK
5
Reviewed on Aug 28, 2019
Before you can run, you must learn to walk.Kasper's well paced tutorials will give you confidence using the tools you need for genomic study.
Recommended if you're interested in Data Science
Johns Hopkins University
Johns Hopkins University
Johns Hopkins University
Johns Hopkins University
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