About this course: 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.
Created by: Johns Hopkins University
Taught by: Kasper Daniel Hansen, PhD, Assistant Professor, Biostatistics and Genetic Medicine
Bloomberg School of Public Health
| Basic Info | Course 6 of 8 in the Genomic Data Science Specialization |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Week One
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.
16 videos, 3 readings
- Reading: Welcome
- Reading: Syllabus
- Reading: Pre Course Survey
- Video: Installing R on A Mac
- Video: Installing R Studio on a Mac
- Video: What is Bioconductor
- Video: Installing Bioconductor
- Video: The Bioconductor Website
- Video: Useful Online Resources
- Video: R Base Types
- Video: GRanges - Overview
- Video: IRanges - Basic Usage
- Video: GenomicRanges - GRanges
- Video: GenomicRanges - Basic GRanges Usage
- Video: GenomicRanges - seqinfo
- Video: AnnotationHub
- Video: Usecase: AnnotationHub and GRanges, part 1
- Video: Usecase: AnnotationHub and GRanges, part 2
Graded: Quiz 1
WEEK 2
Week Two
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.
8 videos
- Video: BSgenome
- Video: Biostrings - Matching
- Video: BSgenome - Views
- Video: GenomicRanges - Rle
- Video: GenomicRanges - Lists
- Video: GenomicFeatures
- Video: rtracklayer - Data Import
Graded: Quiz 2
WEEK 3
Week Three
In this week we will cover Basic Data Types, ExpressionSet, biomaRt, and R S4.
9 videos
- Video: Annotation Overview
- Video: ExpressionSet Overview
- Video: ExpressionSet
- Video: SummarizedExperiment
- Video: GEOquery
- Video: biomaRt
- Video: R S4 Classes
- Video: R S4 Methods
Graded: Quiz 3
WEEK 4
Week Four
In this week, we will cover Getting data in Bioconductor, Rsamtools, oligo, limma, and minfi
7 videos, 1 reading
- Video: Short Read
- Video: Rsamtools
- Video: oligo
- Video: limma
- Video: minfi
- Video: Count-based RNA-seq analysis
- Reading: Post Course Survey
Graded: Quiz 4
FAQs
How It Works
Coursework
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
Help from Your Peers
Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.
Certificates
Earn official recognition for your work, and share your success with friends, colleagues, and employers.
Creators
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Pricing
| Purchase Course | |
|---|---|
| Access to course materials | Available |
| Access to graded materials | Available |
| Receive a final grade | Available |
| Earn a shareable Course Certificate | Available |
Ratings and Reviews
It's very helpful in learning genomic data science. I think it's a little difficult in the beginning. The instructor have some accent, which made me even harder to get into it.
Good course, although some previous experience with R is required and that was not clearly stated beforehand. Moreover it would be better to have a more introductory course to R.
A great introduction to Bioconductor! The course is very hands-on, so be ready to use R extensively.
Coursera provides universal access to the world’s best education,
partnering with top universities and organizations to offer courses online.
© 2018 Coursera Inc. All rights reserved.
The lessons are fairly easy to follow - although the transcript needs re-writing so that the correct words are identified to the speech. I spent a lot of time trying to decipher one or two key words.
The quizzes seemed to test on concepts not yet taught.. perhaps familiar to other Bioinformaticians.. so they were quite tough and required a lot of time to finish.