Who are our courses for:
People who:
Do (or are starting to do) informatics research
Need resources to get started or continue to develop
People who:
Create or maintain scripts for data analysis
Create or maintain full-blown software tools that enable research
People who:
Lead a team
Lead a project
Act as a mentor
Make key decisions
Search for courses that are relevant for you by typing in key words in the search box or the search for each column name. Click on filter arrows next to column names to sort classes.
Note that all of our courses are open source, so all the source material is available on GitHub. All content is licensed with CC-BY 4.0 and therefore reusable with attribution.
This introductory course will provide a quick overview of how the Bayesian NMF algorithm, CoGAPS (Coordinated Gene Activity across Pattern Subsets), can provide new insights into single cell datasets. Through the exercises you will analyze a real dataset using the SciServer compute platform.
The course is intended for anyone seeking a better understanding of current best practices in neoantigen identification and prioritization using pVACtools. It assumes that the learner is familiar with basic biology, genetics and immunology concepts. This course will teach learners to:
Understand key concepts of immunogenomics and neoantigen identification
How to run the pVACtools software suite
How to visualize and prioritize neoantigen candidates with pVACview
This course is an introduction to the immuno workflow on Terra, which leverages a collection of modular WDL workflows for analysis of genomic sequencing data. These enable primary analysis of DNA and RNA-seq data, including for quality control, somatic and germline variant calling, expression analysis, fusion detection, HLA typing, somatic variant allele expression, and immunogenomics approaches for cancer vaccine development (including neoantigen prediction with pVACtools).
This course will introduce background concepts, tools, resources, and relevant standard operating procedures and guidelines for the clinical interpretation of somatic cancer variants.
The course will teach learners to:
Understand key concepts of somatic cancer variant interpretation
Introduce key SOPs and guidelines for classifying the clinical relevance and oncogenicity of somatic cancer variants
Introduce ClinGen Somatic Cancer efforts
Describe somatic variant knowledgebases
Introduce CIViC as a curation platform for somatic variant interpretation
Here you will find all the resources to a course taught through Johns Hopkins: https://jhudatascience.org/intro_to_r/
Recordings of past lectures can be found at the bottom of this page: https://jhudatascience.org/intro_to_r/resources.html
https://www.opencasestudies.org/