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Kasper Daniel Hansen, PhD
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/k3bfoi/bioconductor
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What's inside
Syllabus
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.
Read more
Syllabus
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.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Meets a need in the industry for skilled workers familiar with Bioconductor
Taught by an expert with advanced degrees - PhD in the relevant field
Taught by an experienced instructor - Kasper Daniel Hansen
Taught by experienced instructors from Johns Hopkins University
Quantitative orientation helps learners who prefer to learn through data
Taught by an instructor with extensive background and knowledge in Genomics
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Reviews summary
Bioconductor for genomic data analysis
According to learners, the Bioconductor for Genomic Data Science course offers a highly structured and practical approach to genomic data analysis, with hands-on assignments that reinforce concepts. Many highlight the instructor's ability to simplify complex topics. However, a significant number of students emphasize the steep learning curve, stressing the need for a strong background in R and basic statistics, and ideally some genomics knowledge, as the pace can be fast. While the core content is deemed valuable, some older reviews noted that certain code examples may be outdated, potentially requiring additional troubleshooting. Overall, it's considered a must-take for aspiring bioinformatics professionals, provided they meet the prerequisites.
Instructor simplifies complex topics and provides clear explanations.
"Dr. Leek makes complex topics digestible, and the lectures are concise and to the point."
"The instructor's expertise shines through, making complex topics understandable for me."
"I particularly valued the clear explanations of Bioconductor data structures and how to apply them."
Emphasizes hands-on learning with real-world genomic data.
"The assignments are practical, enabling hands-on learning with real genomic data."
"I really appreciated the focus on application rather than just theory, and the practical examples were excellent."
"The hands-on exercises are well-designed and really reinforce the concepts for me."
"I found the integrated labs solidified my understanding significantly."
Some older code examples and package versions may need updates.
"I think the material is a little dense at times, and some of the older code examples in the notes might need an update..."
"The course has good information, but it feels like it needs an update. Some packages or functions have changed since the course was created..."
"I found getting some practical examples to run locally required a bit of troubleshooting due to environment setup issues."
"I experienced errors in the exercises because some packages or functions have changed."
The course moves quickly, requiring focused attention.
"My main critique is that some parts felt a bit rushed, and I wished for more in-depth examples..."
"The pace was fast, and sometimes the explanations were too brief for me."
"I found it fast-paced, but that's expected for an advanced topic like this."
Requires a solid background in R and genomics for success.
"It’s crucial to have a good grasp of R and basic statistics beforehand..."
"I enrolled hoping to get a practical handle on genomic data, but found this course very difficult. The assumed knowledge was too high for me..."
"I believe a strong intermediate R user will thrive here; it's a must-take for anyone serious about bioinformatics."
"I think this course is only for those with a strong bioinformatics background already, not for a general R user looking to learn genomics."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Bioconductor for Genomic Data Science with these
activities:
Learn to read and comprehend research papers
Show steps
Master the skill of reading and analyzing scientific research papers in bioinformatics.
Browse courses on
Research Methods
Show steps
-
Follow the tutorial on this page https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4998225/
Review statistics used in bioinformatics
Show steps
Start preparing for this course by reviewing the basics of statistical methods used in bioinformatics.
Browse courses on
Bioinformatics
Show steps
-
Read 'Biostatistics: A Foundation for Analysis in the Health Sciences' by Wayne W. Daniel, Chad L. Cross, and John P. Stone
Organize your course materials
Show steps
Maintain a well-organized collection of your course materials for easy access and effective studying.
Show steps
-
Create folders for each module or topic
-
File your notes, assignments, and other materials in the appropriate folders
-
Review your organized materials regularly
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice designing custom bioinformatic pipelines
Show steps
Solidify your understanding of building pipelines for genomic analysis by practicing.
Browse courses on
Bioinformatics
Show steps
-
Start a guided tutorial that follows the section 'How to build bioinformatics pipelines' on this page https://www.biostars.org/p/69114/
Attend a bioinformatics workshop
Show steps
Participate in a workshop to enhance your understanding of cutting-edge techniques and applications in bioinformatics.
Browse courses on
Bioinformatics
Show steps
-
Brainstorm a list of your interests in bioinformatics
-
Research workshops that align with your interests
-
Attend the workshop and actively participate
Become a mentor for other learners
Show steps
Share your knowledge by mentoring other learners in the course.
Show steps
-
Identify opportunities to offer help, such as online forums or study groups
-
Provide guidance, support, and encouragement to other learners
-
Share your own experiences and insights
Attend industry networking events
Show steps
Connect with industry professionals to explore career opportunities and gain insights.
Show steps
Give a Presentation of Bioinformatics to Your Class
Show steps
Present an overview of bioinformatics to your classmates to synthesize your learning and teach others.
Browse courses on
Research Methods
Show steps
-
Prepare slides on the main topics covered in the course
-
Practice your presentation to improve your delivery
-
Get feedback from your peers
Start a small project using bioinformatics tools
Show steps
Apply your knowledge of bioinformatics tools by initiating a project.
Browse courses on
Research Methods
Show steps
-
Identify a problem or question you want to address
-
Research and select appropriate bioinformatics tools
-
Collect and prepare data for analysis
-
Analyze data and interpret results
-
Write a report or presentation summarizing your findings
Learn to read and comprehend research papers
Show steps
Master the skill of reading and analyzing scientific research papers in bioinformatics.
Browse courses on
Research Methods
Show steps
Show steps
Show steps
- Follow the tutorial on this page https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4998225/
Review statistics used in bioinformatics
Show steps
Start preparing for this course by reviewing the basics of statistical methods used in bioinformatics.
Browse courses on
Bioinformatics
Show steps
Show steps
Show steps
- Read 'Biostatistics: A Foundation for Analysis in the Health Sciences' by Wayne W. Daniel, Chad L. Cross, and John P. Stone
Organize your course materials
Show steps
Maintain a well-organized collection of your course materials for easy access and effective studying.
Show steps
Show steps
Show steps
- Create folders for each module or topic
- File your notes, assignments, and other materials in the appropriate folders
- Review your organized materials regularly
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice designing custom bioinformatic pipelines
Show steps
Solidify your understanding of building pipelines for genomic analysis by practicing.
Browse courses on
Bioinformatics
Show steps
Show steps
Show steps
- Start a guided tutorial that follows the section 'How to build bioinformatics pipelines' on this page https://www.biostars.org/p/69114/
Attend a bioinformatics workshop
Show steps
Participate in a workshop to enhance your understanding of cutting-edge techniques and applications in bioinformatics.
Browse courses on
Bioinformatics
Show steps
Show steps
Show steps
- Brainstorm a list of your interests in bioinformatics
- Research workshops that align with your interests
- Attend the workshop and actively participate
Become a mentor for other learners
Show steps
Share your knowledge by mentoring other learners in the course.
Show steps
Show steps
Show steps
- Identify opportunities to offer help, such as online forums or study groups
- Provide guidance, support, and encouragement to other learners
- Share your own experiences and insights
Attend industry networking events
Show steps
Connect with industry professionals to explore career opportunities and gain insights.
Show steps
Show steps
Show steps
Give a Presentation of Bioinformatics to Your Class
Show steps
Present an overview of bioinformatics to your classmates to synthesize your learning and teach others.
Browse courses on
Research Methods
Show steps
Show steps
Show steps
- Prepare slides on the main topics covered in the course
- Practice your presentation to improve your delivery
- Get feedback from your peers
Start a small project using bioinformatics tools
Show steps
Apply your knowledge of bioinformatics tools by initiating a project.
Browse courses on
Research Methods
Show steps
Show steps
Show steps
- Identify a problem or question you want to address
- Research and select appropriate bioinformatics tools
- Collect and prepare data for analysis
- Analyze data and interpret results
- Write a report or presentation summarizing your findings
Career center
Learners who complete Bioconductor for Genomic Data Science will develop knowledge and skills
that may be useful to these careers:
Genomic Data Scientist
Genomic Data Scientist
This course will help build a foundation for a career as a Genomic Data Scientist. This role analyzes genomic data to identify patterns and trends, and to develop new methods for diagnosing and treating diseases.
Biostatistician
Biostatistician
A Biostatistician designs and analyzes studies to evaluate the effectiveness of new treatments and interventions in the field of medicine. This course will help build a foundation in the statistical methods used in biostatistics.
Bioinformatics Analyst
Bioinformatics Analyst
A Bioinformatics Analyst collects, analyzes, and interprets large datasets to identify patterns and trends in biological data. This course will help build a foundation in the computational and statistical methods used in bioinformatics.
Computational Biologist
Computational Biologist
Computational Biology uses computer science, applied mathematics, statistics, and engineering to analyze and interpret biological data. This course will help build a foundation in the computational methods used in computational biology.
Research Scientist
Research Scientist
Research Scientists conduct experiments and analyze data to develop new knowledge and theories in the field of genomics. This course will help build a foundation in the methods used to conduct research in genomics.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify patterns and trends. This course will help build a foundation in the statistical methods used in data analysis.
Statistician
Statistician
Statisticians develop and apply statistical methods to collect, analyze, interpret, and present data. This course will help build a foundation in the statistical methods used in statistics.
Computer Scientist
Computer Scientist
Computer Scientists design, develop, and implement computer systems and applications. This course will help build a foundation in the computational methods used in computer science.
Software Engineer
Software Engineer
Software Engineers design, develop, and implement software systems. This course will help build a foundation in the computational methods used in software engineering.
Systems Analyst
Systems Analyst
Systems Analysts design, develop, and implement computer systems. This course will help build a foundation in the computational methods used in systems analysis.
Database Administrator
Database Administrator
Database Administrators design, develop, and implement database systems. This course will help build a foundation in the computational methods used in database administration.
Network Administrator
Network Administrator
Network Administrators design, develop, and implement computer networks. This course will help build a foundation in the computational methods used in network administration.
Security Analyst
Security Analyst
Security Analysts design, develop, and implement security systems. This course will help build a foundation in the computational methods used in security analysis.
Web Developer
Web Developer
Web Developers design, develop, and implement websites. This course will help build a foundation in the computational methods used in web development.
Technical Writer
Technical Writer
Technical Writers create documentation for computer systems and applications. This course will help build a foundation in the writing skills used in technical writing.
For more career information including salaries, visit:
OpenCourser.com/course/k3bfoi/bioconductor
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Bioconductor for Genomic Data Science.
Covers the concepts of genomic data science by getting into the biological and statistical foundations, big data technologies, open source tools, and analysis methods for the interpretation of genomic data.
Dives deep into the tools commonly used in bioinformatics data science and data carpentry, providing a deep dive into tools.
As a more advanced but still practical resource, this book helps learners get the most out of the Bioconductor workflow.
Save
Provides a practical approach to analyzing data from next-generation sequencing techniques.
Introduces the fundamental principles of genomics, providing a clear and concise overview of the field.
Provides a broad overview of genomics, proteomics, and bioinformatics, introducing the fundamental concepts and techniques used in these fields.
Provides a comprehensive introduction to bioinformatics, covering a wide range of topics from sequence analysis to protein structure prediction.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/k3bfoi/bioconductor
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Rating
3.8
Effort
8 hours to complete
Via
Coursera
Institution
Johns Hopkins University
Instructor
Kasper Daniel Hansen, PhD
Language
English
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