Please familiarize yourself with the programs we will be using in this course. Tutorials are below.
Classes are held from 8:30 AM to 5:00 PM (central time).
| LIVE CONTENT | |||||||
|---|---|---|---|---|---|---|---|
8:30-9:30AM | 9:30AM-12:15PM | 12:15-1:15PM | 1:15-2:45PM | 3:00-5:00PM |
|||
6/24 | Introduction & Lab Setup (self-paced) | Genome Assembly Chris Fields (lecture) | Genome Assembly Lab (self-paced) | Lunch Break | Polymorphisms & Association Tests Alex Lipka (lecture) | Polymorphisms & Association Tests Lab (self-paced) |
|
8:30-10AM | 10:15AM-12:15PM | 12:15-1:15PM | 1:15-2:45PM | 3:00-5:00PM |
|
6/25 | Clinical Variant Interpretation Joe Farris (lecture) | Clinical Variant Interpretation Lab Joe Farris (synchronous) | Lunch Break | RNA-Sequencing Analysis Jessica Holmes (lecture) | RNA-Sequencing Analysis Lab (self-paced) |
6/26 | RNA-Seq in Hereditary Disease Diagnosis & Lab Collin Osborne & Eric Klee (lecture) | Microbiome/Oncobiome Lecture Jun Chen (lecture) | Lunch Break | Basic Single Cell & Spatial Transcriptomics Speaker TBA (lecture) | Single Cell & Spatial Transcriptomics Lab (self-paced) |
6/27 | Clinical Single Cell & Spatial Transcriptomics Yan Asmann (lecture) | Single Cell & Spatial Transcriptomics Lab (self-paced) | Lunch Break | Regulatory Genomics Charles Blatti (lecture) | Regulatory Genomics Lab (self-paced) |
6/28 | AI – Illinois Priyam Mazumdar (lecture) | AI – Illinois Lab Priyam Mazumdar (synchronous) | Lunch Break | AI – Mayo Clinic Irbaz Riaz (lecture) | AI – Mayo Clinic Lab Irbaz Riaz |
| ON DEMAND CONTENT | |||
|---|---|---|---|
| Variant Calling Chris Fields (lecture) | Variant Calling Lab Chris Fields (self-paced) | Systems Biology Charles Blatti (lecture) |
|
15-minute breaks will be given daily at 10:00 AM and 2:45 PM between the lectures and computer labs.
Lab Exercises Data
Pre-Course Tutorials
Sign-in required for Clinical Variant Interpretation laboratory exercise
(free available online tools)
https://franklin.genoox.com/clinical-db/home
https://varsome.com/
Please spend some time familiarizing yourself with the programs we will be using in the course.
RStudio: http://tryr.codeschool.com/ ; http://www.r-tutor.com/r-introduction
Linux/Unix (Tutorial One and Tutorial Two): http://www.ee.surrey.ac.uk/Teaching/Unix/
Google Colab (https://colab.research.google.com/). Note: anyone who doesn’t already have a Google account will need to sign up for one. Setting up an account is quick and easy and can be done here: https://www.google.com/account/about/.
Optional Background Reading
For the Clinical Variant Interpretation Module:
Overview of Specifications to the ACMG/AMP Variant Interpretation Guidelines
https://currentprotocols.onlinelibrary.wiley.com/doi/full/10.1002/cphg.93
Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology
https://www.nature.com/articles/gim201530
For additional information on R and RStudio:
https://moderndive.netlify.pp/1-getting-started.html
For the module on Systems Biology:
KnowEnG system: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000583 (associated web site is: https://knoweng.org/analyze/)
For the module on “RNAseq in Hereditary Disease Diagnosis”:
Improving genetic diagnosis in Mendelian disease with transcriptome sequencing:
https://stm.sciencemag.org/content/9/386/eaal5209.short
OUTRIDER: A Statistical Method for Detecting Aberrantly Expressed Genes in RNA Sequencing Data:
https://www.sciencedirect.com/science/article/pii/S0002929718304014
LeafCutterMD: an algorithm for outlier splicing detection in rare diseases:
https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btaa259/5823301
A tailored approach to fusion transcript identification increases diagnosis of rare inherited disease:
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223337