The course is intended for students in the biomedical sciences and researchers who have been given data and don’t know what to do with it or would like an overview of the different genomic data types that are out there.
This course is written for individuals who:
- Have genomic data and don’t know what to do with it.
- Want a basic overview of genomic data types.
- Want to find resources for processing and interpreting genomics data.
Goal of this course:
Read more
The course is intended for students in the biomedical sciences and researchers who have been given data and don’t know what to do with it or would like an overview of the different genomic data types that are out there.
This course is written for individuals who:
- Have genomic data and don’t know what to do with it.
- Want a basic overview of genomic data types.
- Want to find resources for processing and interpreting genomics data.
Goal of this course:
The course is intended for students in the biomedical sciences and researchers who have been given data and don’t know what to do with it or would like an overview of the different genomic data types that are out there.
This course is written for individuals who:
- Have genomic data and don’t know what to do with it.
- Want a basic overview of genomic data types.
- Want to find resources for processing and interpreting genomics data.
Goal of this course:
Equip learners with tutorials and resources so they can understand and interpret their genomic data in a way that helps them meet their goals and handle the data properly. This includes helping learners formulate questions they will need to ask others about their data
What is not the goal
Teach learners about choosing parameters or about the ins and outs of every genomic tool they might be interested in. This course is meant to connect people to other resources that will help them with the specifics of their genomic data and help learners have more efficient and fruitful discussions about their data with bioinformatic experts.
The course is intended for students in the biomedical sciences who have been given data and don’t know what to do with it or would like an overview of the different genomic data types that are out there.
What's inside
Syllabus
Introduction
In this module, we cover the basics of what will be covered in this course and what you should expect. Next we get into an overview of what omic data types and their workflows often look like.
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Syllabus
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Activities
Review Basic Statistics and Probability
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Strengthen your foundation by revisiting essential statistical and probability concepts used in omic data analysis.
Browse courses on
Statistics
Show steps
-
Review your notes or textbooks on basic statistics and probability.
-
Solve practice problems to test your understanding.
Compile a Glossary of Omic Data Terminology
Show steps
Deepen your understanding of omic data by creating a comprehensive glossary of key terms and concepts.
Show steps
-
Review course materials and identify unfamiliar terms.
-
Search for definitions in textbooks, online resources, and scientific papers.
-
Organize the terms into a structured glossary, such as a spreadsheet or wiki.
Explore the Bioconductor Project
Show steps
Reinforce your understanding of omic data workflows by exploring the widely-used Bioconductor Project.
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Bioinformatics
Show steps
-
Visit the Bioconductor website and browse the available packages.
-
Identify a package relevant to your research interests.
-
Follow the tutorials provided for the package to gain hands-on experience.
Four other activities
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Show all seven activities
Form a Study Group for Omic Data Analysis
Show steps
Enhance your learning by collaborating with classmates and discussing omic data analysis concepts and challenges.
Show steps
-
Identify classmates who share your interests and learning goals.
-
Establish a regular meeting schedule and meeting format.
-
Prepare discussion topics and assignments to facilitate knowledge sharing.
Practice Data Wrangling with R and Bioconductor
Show steps
Solidify your data manipulation skills by practicing with real-world genomic datasets using R and Bioconductor.
Browse courses on
Data Wrangling
Show steps
-
Find a public genomic dataset that aligns with your interests.
-
Load the data into R using appropriate Bioconductor packages.
-
Perform data cleaning and preprocessing steps.
-
Explore the data using visualizations and statistical tests.
Attend a Bioinformatics Workshop
Show steps
Gain practical experience and connect with experts by attending a workshop focused on omic data analysis techniques.
Browse courses on
Genomics
Show steps
-
Search for upcoming bioinformatics workshops in your area.
-
Select a workshop that aligns with your interests and skill level.
-
Actively participate in the workshop and engage with the instructors.
Develop a Data Analysis Plan for an Omic Data Project
Show steps
Apply your knowledge by creating a detailed plan for analyzing a real-world omic dataset, ensuring a structured and efficient approach.
Show steps
-
Define the research question and objectives.
-
Select appropriate data analysis methods and tools.
-
Outline the steps of the analysis workflow.
-
Consider potential challenges and mitigation strategies.
Review Basic Statistics and Probability
Show steps
Strengthen your foundation by revisiting essential statistical and probability concepts used in omic data analysis.
Browse courses on
Statistics
Show steps
- Review your notes or textbooks on basic statistics and probability.
- Solve practice problems to test your understanding.
Compile a Glossary of Omic Data Terminology
Show steps
Deepen your understanding of omic data by creating a comprehensive glossary of key terms and concepts.
Show steps
- Review course materials and identify unfamiliar terms.
- Search for definitions in textbooks, online resources, and scientific papers.
- Organize the terms into a structured glossary, such as a spreadsheet or wiki.
Explore the Bioconductor Project
Show steps
Reinforce your understanding of omic data workflows by exploring the widely-used Bioconductor Project.
Browse courses on
Bioinformatics
Show steps
- Visit the Bioconductor website and browse the available packages.
- Identify a package relevant to your research interests.
- Follow the tutorials provided for the package to gain hands-on experience.
Form a Study Group for Omic Data Analysis
Show steps
Enhance your learning by collaborating with classmates and discussing omic data analysis concepts and challenges.
Show steps
- Identify classmates who share your interests and learning goals.
- Establish a regular meeting schedule and meeting format.
- Prepare discussion topics and assignments to facilitate knowledge sharing.
Practice Data Wrangling with R and Bioconductor
Show steps
Solidify your data manipulation skills by practicing with real-world genomic datasets using R and Bioconductor.
Browse courses on
Data Wrangling
Show steps
- Find a public genomic dataset that aligns with your interests.
- Load the data into R using appropriate Bioconductor packages.
- Perform data cleaning and preprocessing steps.
- Explore the data using visualizations and statistical tests.
Attend a Bioinformatics Workshop
Show steps
Gain practical experience and connect with experts by attending a workshop focused on omic data analysis techniques.
Browse courses on
Genomics
Show steps
- Search for upcoming bioinformatics workshops in your area.
- Select a workshop that aligns with your interests and skill level.
- Actively participate in the workshop and engage with the instructors.
Develop a Data Analysis Plan for an Omic Data Project
Show steps
Apply your knowledge by creating a detailed plan for analyzing a real-world omic dataset, ensuring a structured and efficient approach.
Show steps
- Define the research question and objectives.
- Select appropriate data analysis methods and tools.
- Outline the steps of the analysis workflow.
- Consider potential challenges and mitigation strategies.
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