The 2024 schedule will be similar to the schedule below.
Please familiarize yourself with the programs we will be using in this course. Tutorials are below.
Here is a link to a video explaining how to connect to the IGB biocluster using mac terminal instead of MobaXterm for mac users.
Classes are held from 8:30 AM to 5:00 PM (central time).
Live Content
| 8:30-10AM | 10:15AM-12:15PM | 12:15-1:15PM | 1:15-2:45PM | 3:00-5:00PM | |
| 6/20 Tues | Lab set-up/Unix Lab pdf pptx Set Up VM (UIUC) Set Up VM (Mayo) (self-paced) | Statistics Lecture & Lab Dave Zhao R script (synchronous) | Lunch Break | Genome Assembly Chris Fields pdf pptx (lecture) | Genome Assembly Lab pdf pptx (self-paced) |
| 6/21 Wed | RNA-Sequencing Analysis Jessica Holmes pdf pptx (lecture) | RNA-Sequencing Analyses Lab pdf pptx (self-paced) | Lunch Break | Medical AI Challenges & Opportunities Garrett Jenkinson pdf pptx (lecture) | RNA-Seq in Hereditary Disease Diagnosis & Lab Eric Klee RNA-Seq: pdf pptx Outlier: pdf pptx (lecture & lab) |
| 6/22 Thu | Variant Calling Chris Fields pdf pptx (lecture) | Variant Calling Lab pdf pptx (self-paced) | Lunch Break | Polymorphisms & Association Tests Alex Lipka pdf pptx (lecture) | Polymorphisms & Association Tests Lab pdf pptx (self-paced) |
| 6/23 Fri | Clinical Variant Interpretation Matheus Wilke pdf pptx (lecture) | Clinical Variant Interpretation Lab Matheus Wilke pptx (synchronous) | Lunch Break | Systems Biology Charles Blatti pdf pptx (lecture) | Systems Biology Lab pdf pptx (self-paced) |
On Demand Content
| Regulatory Genomics Saurabh Sinha pptx (lecture) | Regulatory Genomics Lab Saurabh Sinha pptx (self-paced) | Data Mining & Informatics Krishna Rani Kalari pptx (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