Level 1: Install Essential Tools
Students begin by learning how to install the necessary software for bioinformatic analyses. This foundational step will provide you with essential software for any computational...
Computational Genomics Lab
Open Source Teaching
Free Practical Bioinformatics for Everyone!
Computational genomics combines computer science and biology to analyze diverse genome-wide data sets to triangulate insights into gene regulation and function. Our Computational Genomics Lab Course brought to you by the Rinn Lab, is designed to teach students how to perform bioinformatic analyses on data like RNA-seq and ATAC-seq. We want to empower learners by learning the fundamental skills while applying them to real world genomics research questions. We aim to provide a real-world bioinformatics experience that can be applied to future career or research goals – even job applications!
Our course is accessible online for free to anyone interested in Bioinformatics and or genomics. No skills required and minimal computer power needed!
Class Website (in video game-ish format)
ALL RNAseq, ATACseq, and Genome Annotation files needed to participate are here.
Empowering Learning Through Hands-On Experience
The course includes ten levels, each focusing on specific tools and techniques important for RNA biology and epigenetic research. Students move from basic setup and data management to advanced analysis and visualization. We build confidence and competence by guiding students step-by-step through workflows used in cutting-edge research. Our lessons use real-world datasets so learners can apply what they learn directly to meaningful genomic questions.
Level 2: SSH Connect & Set Up Git
In this level, students gain skills in securely connecting to remote servers using SSH. They also learn how to set up Git for version control,...
Level 3: Flowing with Next Flow
Students discover how to streamline their RNA-seq analysis pipelines by using Next Flow. This tool allows for automation and improves the speed and reliability of...
Level 4: RNAseq Pipeline!
This level teaches students to process raw RNA-seq sequence data through to the analyzed results. They learn the standard steps involved in preparing RNA-seq data...
Level 5: R RNAseq Output
Learners develop skills in interpreting RNA-seq results and visualizing the data using the R programming language. This helps in communicating findings clearly.
Level 6: Analyze RNAseq data
Students perform detailed analysis to extract meaningful scientific conclusions from RNA-seq experiments. This level emphasizes critical thinking and data interpretation.
Level 7: GGPLOT Making Figures
This level focuses on mastering figure creation with GGPLOT. Students learn to make clear and informative visual representations of RNA-seq and genomics data.
Level 8: ATACseq Pipeline
Students learn to analyze chromatin accessibility data obtained from ATAC-seq experiments. This helps reveal regulatory regions of the genome.
Level 9: ATACseq & The Genome
At this level, learners understand how chromatin accessibility relates to genome structure and function. They explore the biological implications of ATAC-seq data.
Level 10: Choose your own adventure!
Congratulations !! You are now a proficient bioinformatician !! Now set out to explore more - there is all the same data we analyzed in...
