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Researcher's guide to RNA sequencing data

3.6 Filled star Filled star Filled star Half star Empty star
Based on 17 ratings
see reviews
Candace Savonen, MS

This course is a follow up course to "Choosing genomics tools" which dives into further detail about RNA informatics methods!

This course is for individuals who:

- Have taken Researcher's Guide to Fundamentals of Omic Data

- Have RNA data and don’t know what to do with it.

- Want a basic overview of their RNA focused data type.

- Want to find resources for processing and interpreting RNA data

What this course will cover:

- Fundamentals of RNA methods.

- Resources you may consider looking into for your own purposes.

Read more

This course is a follow up course to "Choosing genomics tools" which dives into further detail about RNA informatics methods!

This course is for individuals who:

- Have taken Researcher's Guide to Fundamentals of Omic Data

- Have RNA data and don’t know what to do with it.

- Want a basic overview of their RNA focused data type.

- Want to find resources for processing and interpreting RNA data

What this course will cover:

- Fundamentals of RNA methods.

- Resources you may consider looking into for your own purposes.

- Questions you should ask yourself and your colleagues about your goals and experimental design.

What this course will NOT cover:

- Code needed to process your data.

- Details about every type of experimental design.

- Everything you’d need to know to make you a computational biologist. In other words we still highly encourage you to consult your informatics and computational colleagues, especially those who may have done any handling of data you are trying to learn about.

Enroll now

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What's inside

Syllabus

Introduction
In this first module we introduce the goals of this course an do an overview of the available methods for RNA methods, otherwise known as gene expression.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Provides foundational understanding of RNA methods for gene expression analysis
Suitable for learners with prior experience in genomics tools and RNA data
Emphasizes resources, tools, and considerations for RNA data analysis
Covers various RNA sequencing methods, including bulk, single cell, and spatial transcriptomics
Does not delve into technical details, such as coding or specific experimental designs
Taught by an experienced instructor specializing in omics data informatics

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Reviews summary

Researcher's essential rna-seq conceptual guide

According to students, this course offers a fantastic overview of RNA sequencing methods, including Bulk RNA-seq, Single Cell RNA-seq, and Spatial Transcriptomics. Learners commend its clear explanations and strong focus on experimental design questions, proving highly valuable for research planning. It's especially praised as a strong conceptual guide, aiding wet-lab scientists in understanding the field and communicating with bioinformaticians. While explicitly not covering code, some reviewers expressed a desire for more practical examples or deeper application beyond the theoretical. Overall, the course is well-structured and effectively achieves its stated goals as a guide, not a coding bootcamp.
Organized and easy to follow course modules.
"The content is well-structured and easy to follow."
"Very informative. The explanations for Bulk, scRNA-seq, and Spatial Transcriptomics were clear and distinct."
Helps non-computational researchers bridge knowledge gaps.
"As someone who inherited RNA data, this course was a lifesaver. It didn't make me a bioinformatician, but it gave me the language to talk to my computational colleagues..."
"Highly recommended for wet-lab scientists."
"It certainly achieved its goal of providing a strong conceptual guide, not a coding boot camp."
Provides excellent clarity on RNA-seq methods.
"This course was an absolutely fantastic overview of RNA sequencing methods. I appreciated the clear explanations..."
"A solid introduction to RNA-seq. It covered the core concepts well, particularly liked the module on single-cell."
"Excellent course for researchers. It clarifies the 'why' behind different RNA-seq techniques and emphasizes critical thinking about experimental setup."
Some found the course too high-level and superficial.
"Good course, but a bit too high-level for my needs."
"I found this course somewhat disappointing. While it gives an overview, it doesn't go deep enough into any one method."
"It felt like scratching the surface."
Desired more practical examples or coding guidance.
"...it explicitly states no code, which is fair, but I wish there were at least pointers to resources for the actual data analysis..."
"Good course, but a bit too high-level for my needs. I was hoping for more practical examples or case studies, even without code."
"While it explains the methods, applying them feels like a separate hurdle."

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 Researcher's guide to RNA sequencing data with these activities:
Review the structure and function of RNA
Refresh your knowledge of the structure and function of RNA, including the different types of RNA molecules and their roles in gene expression.
Show steps
  • Read a textbook chapter or online article on RNA structure and function.
  • Watch a video tutorial on RNA structure.
Review Bulk RNA-seq
Refresh your knowledge of Bulk RNA-seq methods to solidify your understanding of gene expression of tissue.
Show steps
  • Go over foundational principles of Bulk RNA-seq.
  • Review protocols and pipelines for Bulk RNA-seq.
Review RNA sequencing (RNA-seq)
Refreshing your knowledge of the RNA-Seq technique is essential for getting the most out of this course.
Browse courses on RNA-seq
Show steps
  • Re-read the basic principles of RNA-Seq.
  • Go over the different types of RNA-Seq experiments.
  • Review the data analysis workflow for RNA-Seq.
22 other activities
Expand to see all activities and additional details
Show all 25 activities
Review basic methods of gene expression
Refresh your knowledge of the basic methods used to measure gene expression, such as RNA sequencing and microarrays.
Browse courses on Gene Expression
Show steps
  • Read a textbook chapter or online article on RNA sequencing.
  • Watch a video tutorial on how to perform RNA sequencing.
  • Complete a practice exercise on RNA sequencing data analysis.
Discuss RNA-seq Analysis Techniques
Gain diverse perspectives and insights into RNA-seq analysis techniques through discussions with peers.
Browse courses on RNA-Seq Analysis
Show steps
  • Connect with classmates or peers in the field.
  • Host or join study groups to discuss specific RNA-seq analysis methods.
Review RNA extraction techniques
Reviewing RNA extraction techniques will refresh your memory on the proper procedures and ensure that you have a solid foundation for the course.
Browse courses on RNA Sequencing
Show steps
  • Read articles or watch videos on RNA extraction techniques.
  • Practice RNA extraction on a sample.
Identify a Mentor in the Field of RNA Bioinformatics
Gain access to expert guidance and support by identifying a mentor in the field of RNA Bioinformatics.
Browse courses on RNA Sequencing
Show steps
  • Research potential mentors at universities or research institutions.
  • Reach out to potential mentors via email or LinkedIn.
Follow tutorials on RNA analysis software
Following tutorials on RNA analysis software will introduce you to the tools and techniques used in the course, giving you a head start.
Show steps
  • Identify a tutorial on an RNA analysis software tool.
  • Follow the tutorial step-by-step, practicing the commands and techniques.
Learn about gene expression microarrays
This activity will help you understand the basics of gene expression microarrays, which is a closely related technique to RNA-Seq.
Browse courses on Microarrays
Show steps
  • Find an online tutorial about gene expression microarrays.
  • Follow the tutorial to learn about the principles of microarrays.
  • Watch a video demonstration of a microarray experiment.
Follow a tutorial on spatial transcriptomics
Spatial transcriptomics is a newer method for evaluating gene expression that provides spatial information. This tutorial will help you learn the basics of spatial transcriptomics.
Show steps
  • Find a tutorial on spatial transcriptomics
  • Follow the tutorial step-by-step
  • Complete the exercises or assignments included in the tutorial
Interpret Spatial Transcriptomics Data
Develop your ability to analyze gene expression of tissue with spatial information by interpreting Spatial Transcriptomics data.
Show steps
  • Gather various sample Spatial Transcriptomics datasets.
  • Practice interpreting the data to identify patterns and insights.
Participate in a study group
Participating in a study group will provide you with opportunities to discuss course concepts, ask questions, and learn from others.
Show steps
  • Find a study group or start your own with classmates.
  • Meet regularly to discuss course material, work on assignments, and prepare for exams.
Practice analyzing RNA sequencing data
Practice your skills in analyzing RNA sequencing data to identify differentially expressed genes and other patterns of gene expression.
Browse courses on Gene Expression Analysis
Show steps
  • Download an RNA sequencing dataset from a public repository.
  • Use a software package to analyze the dataset and identify differentially expressed genes.
  • Interpret the results of your analysis and write a brief report.
Practice Bulk RNA-seq techniques
Bulk RNA-seq is a common method for evaluating gene expression. This practice will help reinforce learning from the Bulk RNA-seq module.
Browse courses on RNA-seq
Show steps
  • Review the Bulk RNA-seq module materials
  • Use an online tool or software to practice analyzing Bulk RNA-seq data
  • Join a discussion forum or online community to discuss Bulk RNA-seq techniques with other learners
Enroll in a Single Cell RNA-seq Tutorial
Supplement your understanding of gene expression of single cells by exploring Single Cell RNA-seq methods.
Show steps
  • Find reputable Single Cell RNA-seq tutorials online.
  • Follow the tutorial, making notes and asking questions as needed.
Create a visualization of Single Cell RNA-seq data
Creating a visualization of Single Cell RNA-seq data will help you understand the relationships between different cell types and their gene expression profiles.
Browse courses on RNA-seq
Show steps
  • Review the Single Cell RNA-seq module materials
  • Use a visualization tool or software to create a visualization of Single Cell RNA-seq data
  • Share your visualization with others and get feedback
Summarize course lectures
Creating summaries of course lectures will help you retain information and identify key concepts.
Show steps
  • After each lecture, take notes on the main points.
  • Within 24 hours, expand your notes into a concise summary.
  • Review your summaries regularly to reinforce your understanding.
Practice interpreting RNA-Seq data
This activity will give you hands-on experience with interpreting RNA-Seq data.
Browse courses on RNA-seq
Show steps
  • Download a publicly available RNA-Seq dataset.
  • Use a software package to analyze the dataset.
  • Write a report summarizing your findings.
Develop a research proposal using RNA methods
This will help you apply the concepts you have learned in the course to a real-world research question.
Show steps
  • Identify a research question that you are interested in
  • Develop a hypothesis and specific aims
  • Choose the appropriate RNA methods to use
  • Design your experiment
  • Write a research proposal
Explore Gene Expression Microarrays
Expand your knowledge in gene expression analysis by familiarizing yourself with Gene Expression Microarrays.
Show steps
  • Find educational resources on Gene Expression Microarrays.
  • Review the principles, methods, and applications of microarrays.
Practice RNA analysis problems
Solving RNA analysis problems will improve your understanding of the concepts and techniques covered in the course.
Browse courses on Data Interpretation
Show steps
  • Find practice problems online or in textbooks.
  • Attempt to solve the problems on your own.
  • Check your solutions against the provided answer key.
Create a Visual Representation of RNA-seq Results
Enhance your understanding of RNA-seq results by creating a visual representation of the data.
Browse courses on RNA-seq
Show steps
  • Select appropriate data visualization tools for your chosen data.
  • Create visualizations that effectively communicate the key findings of your RNA-seq analysis.
Create a visualization for your RNA-Seq data
This activity will help you to improve your data visualization skills and communicate your findings more effectively.
Browse courses on RNA-seq
Show steps
  • Choose a type of visualization that is appropriate for your data.
  • Use a software package to create the visualization.
  • Present your visualization to your classmates or colleagues.
Design an Experiment Using RNA-seq Data
Apply your understanding of RNA-seq data by designing an experiment that utilizes it.
Browse courses on RNA-seq
Show steps
  • Identify a specific research question you want to address.
  • Determine the appropriate RNA-seq approach for your experiment.
  • Design the experiment, including sample preparation, sequencing parameters, and data analysis methods.
Create a research proposal on an RNA-related topic
Creating a research proposal will allow you to apply the knowledge and skills learned in the course to a real-world problem.
Browse courses on Research Proposal
Show steps
  • Identify a research question related to RNA.
  • Research the topic, including relevant literature and data.
  • Write a proposal outlining your research question, methods, and expected outcomes.

Career center

Learners who complete Researcher's guide to RNA sequencing data will develop knowledge and skills that may be useful to these careers:

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Course image
Rating
3.6 Filled star Filled star Filled star Half star Empty star
Effort
4 hours to complete
Level
Intermediate
Via
Coursera
Institution
Fred Hutchinson Cancer Center
Instructor
Candace Savonen, MS
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Provides foundational understanding of RNA methods for gene expression analysis
Suitable for learners with prior experience in genomics tools and RNA data
Emphasizes resources, tools, and considerations for RNA data analysis
Covers various RNA sequencing methods, including bulk, single cell, and spatial transcriptomics
Does not delve into technical details, such as coding or specific experimental designs
Taught by an experienced instructor specializing in omics data informatics
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