Learning Resources
Tutorials, workshop resources, and examples for learning how to run your research computing work at scale. Filter by topic using the tags or search for a keyword. Have a resource to contribute? Fill out our contribution form.
Showing 8 of 8 guides
Predict Protein Structures with Alphafold3
AlphaFold3 (AF3) predicts atomic-resolution biomolecular structures for proteins, nucleic acids, and complexes.
Learn How to Deploy R Calculations
A step-by-step example of transitioning from running R calculations on your computer using RStudio, to running many such calculations on a HTC system.
Build a Conda-based Container for Bioinformatics
This tutorial covers the basics of how to use containers to deploy software. While this example is bioinformatics-flavored, the concepts can be applied to any software stack.
Genome Assembly using Nanopore Reads on CHTC
A genome assembly workflow for Oxford Nanopore long reads using hifiasm on CHTC's High Throughput Computing infrastructure.
Using ResearchDrive with CHTC
Learn how to use the computing power of CHTC with the data you keep in ResearchDrive.
Cat-Dog Classifier: Run a PyTorch workflow on the HTC system
Learn how to run PyTorch training and inference workflows with this cat-dog image classifier. Contains example container recipes that you can use as a starting point for your own ML workflows.
Analyzing Multiple Sequence Files with fastqc
How to run a set of jobs using different input files, with bioinformatics as the example domain. This process can be applied to any other workflow that processes individual data files.
Automating Job Submission with HTCondor's DAGMan
HTCondor's Directed Acyclic Graph Manager (DAGMan) utility enables you to automate the submission of your HTCondor jobs. This tutorial guides you through how to use DAGMan to submit two HTCondor jobs.