Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University.
This course is part of the Genomic Data Science Specialization
Command Line Tools for Genomic Data Science
Offered By
About this Course
19,112 recent views
Skills you will gain
BioinformaticsSamtoolsUnixCommand-Line Interface
Syllabus - What you will learn from this course
Week
13 hours to complete
Basic Unix Commands
In this module, you will be introduced to command Line Tools for Genomic Data Science
12 videos (Total 105 min), 5 readings, 2 quizzes
12 videos
Basic Unix Commands 2: Files, Directories, Paths7m
Basic Unix Commands 3: File Naming4m
Basic Unix Commands 4: Content Creation9m
Basic Unix Commands 5: Accessing Content I6m
Basic Unix Commands 6: Accessing Content II4m
Basic Unix Commands 7: Redirecting Content6m
Basic Unix Commands 8: Querying Content15m
Basic Unix Commands 9: Comparing Content11m
Basic Unix Commands 10: Archiving Content13m
Basic Unix Commands 11: Practical Exercises I13m
Basic Unix Commands 12: Practical Exercises II9m
5 readings
Welcome Message10m
Syllabus10m
VMBox Download & Instructions10m
Pre-Course Survey10m
Module 1 Exam Instructions **IMPORTANT**10m
2 practice exercises
Module 1 Quiz20m
Module 1 Exam34m
Week
23 hours to complete
Week Two
In this module, we'll be taking a look at Sequences and Genomic Features in a sequence of 10 presentations.
11 videos (Total 127 min), 1 reading, 2 quizzes
11 videos
Sequences and Genomic Features 2: Sequence Representation and Generation11m
Sequences and Genomic Features 3: Annotation14m
Sequences and Genomic Features 4.1: Alignment I13m
Sequences and Genomic Features 4.2: Alignment II9m
Sequences and Genomic Features 5: Recreating Sequences & Features12m
Sequences and Genomic Features 6: Genomic Feature Retrieval5m
Sequences and Genomic Features 7: SAMtools I11m
Sequences and Genomic Features 8: SAMtools II9m
Sequences and Genomic Features 9: BEDtools I15m
Sequences and Genomic Features 10: BEDtools II15m
1 reading
Module 2 Exam Instructions **IMPORTANT**10m
2 practice exercises
Module 2 Quiz20m
Module 2 Exam40m
Week
32 hours to complete
Week Three
In this module, we'll be going over Alignment and Sequence Variation in another sequence of 8 presentations.
8 videos (Total 55 min), 1 reading, 2 quizzes
8 videos
Alignment & Sequence Variation 2: Alignment & Variant Detection Tools5m
Alignment & Sequence Variation 3: VCF11m
Alignment & Sequence Variation 4: Bowtie9m
Alignment & Sequence Variation 5: BWA 4m
Alignment & Sequence Variation 6: SAMtools (mpileup)6m
Alignment & Sequence Variation 7: BCFtools8m
Alignment & Sequence Variation 8: Variant Calling5m
1 reading
Module 3 Exam Instructions **IMPORTANT**10m
2 practice exercises
Module 3 Quiz20m
Module 3 Exam48m
Week
43 hours to complete
Week Four
In this module, we'll be going over Tools for Transcriptomics in a sequence of 6 presentations.
8 videos (Total 75 min), 2 readings, 2 quizzes
8 videos
Tools for Transcriptomics 2: RNA-seq7m
Tools for Transcriptomics 3.1: Tophat I9m
Tools for Transcriptomics 3.2: Tophat II 8m
Tools for Transcriptomics 4: Cufflinks10m
Tools for Transcriptomics 5: Cuffdiff16m
Tools for Transcriptomics 6.1: Integrated Genomics Viewer I8m
Tools for Transcriptomics 6.2: Integrated Genomics Viewer II 6m
2 readings
Module 4 Exam Instructions **IMPORTANT**10m
Post-Course Survey10m
2 practice exercises
Module 4 Quiz20m
Module 4 Exam1h 10m
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Top reviews from Command Line Tools for Genomic Data Science
Thank you very much Dr./Professor, Liliana Florea. I've learned a lot. It's a very good opportunity to improve my knowledge. This means a lot to me.
Very informative course. Because I am new to this, it was at times confusing. But overall, great teaching and great experience. Thank you.
Instructor
Liliana Florea, PhD
Assistant ProfessorMcKusick-Nathans Institute of Genetic Medicine
About 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.
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?
Is financial aid available?
More questions? Visit the Learner Help Center.
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