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.
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Genomic Data Science SpecializationJohns Hopkins UniversityAbout this Course
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Course 6 of 8 in the
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Approx. 8 hours to complete
English
Subtitles: English
Skills you will gain
BioinformaticsBioconductorGenomicsR Programming
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 6 of 8 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 8 hours to complete
English
Subtitles: English
Offered by
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.
Syllabus - What you will learn from this course
3 hours to complete
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.
3 hours to complete
16 videos (Total 126 min), 3 readings, 1 quiz
16 videos
Installing R on A Mac 2m
Installing R Studio on a Mac 1m
What is Bioconductor7m
Installing Bioconductor3m
The Bioconductor Website9m
Useful Online Resources5m
R Base Types18m
GRanges - Overview4m
IRanges - Basic Usage12m
GenomicRanges - GRanges8m
GenomicRanges - Basic GRanges Usage8m
GenomicRanges - seqinfo6m
AnnotationHub8m
Usecase: AnnotationHub and GRanges, part 112m
Usecase: AnnotationHub and GRanges, part 213m
3 readings
Welcome10m
Syllabus10m
Pre Course Survey10m
1 practice exercise
Quiz 120m
2 hours to complete
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.
2 hours to complete
8 videos (Total 81 min)
8 videos
BSgenome6m
Biostrings - Matching6m
BSgenome - Views9m
GenomicRanges - Rle12m
GenomicRanges - Lists6m
GenomicFeatures18m
rtracklayer - Data Import14m
1 practice exercise
Quiz 220m
2 hours to complete
Week Three
In this week we will cover Basic Data Types, ExpressionSet, biomaRt, and R S4.
2 hours to complete
9 videos (Total 79 min)
9 videos
Annotation Overview4m
ExpressionSet Overview4m
ExpressionSet9m
SummarizedExperiment7m
GEOquery6m
biomaRt13m
R S4 Classes16m
R S4 Methods10m
1 practice exercise
Quiz 320m
2 hours to complete
Week Four
In this week, we will cover Getting data in Bioconductor, Rsamtools, oligo, limma, and minfi
2 hours to complete
7 videos (Total 81 min), 1 reading, 1 quiz
7 videos
Short Read4m
Rsamtools12m
oligo14m
limma16m
minfi11m
Count-based RNA-seq analysis15m
1 reading
Post Course Survey10m
1 practice exercise
Quiz 420m
About the Genomic Data Science Specialization
With genomics sparks a revolution in medical discoveries, it becomes imperative to be able to better understand the genome, and be able to leverage the data and information from genomic datasets. Genomic Data Science is the field that applies statistics and data science to the genome.
This Specialization covers the concepts and tools to understand, analyze, and interpret data from next generation sequencing experiments. It teaches the most common tools used in genomic data science including how to use the command line, along with a variety of software implementation tools like Python, R, Bioconductor, and Galaxy.
This Specialization is designed to serve as both a standalone introduction to genomic data science or as a perfect compliment to a primary degree or postdoc in biology, molecular biology, or genetics, for scientists in these fields seeking to gain familiarity in data science and statistical tools to better interact with the data in their everyday work.
To audit Genomic Data Science courses for free, visit https://www.coursera.org/jhu, click the course, click Enroll, and select Audit. Please note that you will not receive a Certificate of Completion if you choose to Audit.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
Will I earn university credit for completing the Course?
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.
More questions? Visit the Learner Help Center.
