The goal of the Applied Bioinformatics Course is to provide hands-on training on major bioinformatics resources through the analysis of an RNA-Seq data set to find differentially expressed genes and investigate previously described functions of those genes and the pathways in which they are involved.
Topics include web-based gene and protein resources, genome browsers, pathways and gene set enrichment analyses, and RNA-Seq data analysis. RNA-Seq data analysis will be conducted using CLC Genomics Workbench, the web-based Galaxy system, R statistical computing environment and Ingenuity Pathways Analysis. The course will feature several modules that will have written worked examples to demonstrate how to apply the major tools or resources featured in the module. Participants should have a strong background in molecular biology. Prior computer programming skills are not required, but participants need to have a strong interest in learning some programming concepts.
Tuition includes on-campus double-occupancy housing and meals. Single occupancy, if available, may be purchased for an additional fee.
2017 tuition – Students/postdocs: $1,200.00; faculty/professionals $1,600.00
Sample schedule, subject to change
Day 1 (Introduction)
4:00 pm – 5:00 pm – Housing check in
6:00 pm – 7:00 pm Dinner
7:00 pm – 9:00 pm – Course Introduction and Overview
Day 2 (Sequence Analysis)
7:00 am – 9:00 am Self-Serve Breakfast
9:00 am – 10:30 am – Introduction to High-Throughput Sequencing
10:30 am – 10:45 am – Break
10:45 am – 12:00 pm – Overview of Sequence Analysis Workflow
12:00 pm – 1:00 pm – Lunch
1:00 pm – 2:30 pm – Read Alignment and Analysis Workshop (Part 1)
2:30 pm – 3:00 pm – Break
3:00 pm – 6:00 pm – Read Alignment and Analysis Workshop (Part 2)
6:00 pm – 7:00 pm – Dinner
7:00 pm – 8:00 pm – Keynote Lecture
Day 3 (Gene, Protein and Sequence Tools)
7:00 am – 9:00 am Self-Serve Breakfast
9:00 am – 10:30 am – Gene, Protein and Sequence Resources
10:30 am – 10:45 am – Break
10:45 am – 12:00 pm – Genome Browsers & Data Retrieval
12:00 pm – 1:00 pm – Lunch
1:00 pm – 2:00 pm – Analysis of High Throughput Data
2:00 pm – 2:45 pm – R Power Tools: Way Beyond Word & Excel
2:45 pm – 3:15 pm – Break
3:15 pm – 4:00 pm – Introduction to R Studio
4:00 pm – 5:00 pm – R Statistical Computing Environment I
6:00 pm – 7:00 pm – Dinner (Dining Hall)
7:00 pm – 8:00 pm – Large-Scale Computing for Genomics
Day 4 (R Statistical Computing Environment)
7:00 am – 9:00 am Self-Serve Breakfast
9:00 am – 10:00 am – R Statistical Computing Environment II
10:00 am – 10:45 am – Advanced R and Exploratory Data Analysis I
10:45 am – 11:00 am – Break
11:00 am – 12:00 pm – Advanced R and Exploratory Data Analysis II
12:00 pm – 1:00 pm – Lunch
1:00 pm – 2:45 pm – EdgeR and Differential Expression
2:45 pm – 3:15 pm – Break
3:15 pm – 5:00 pm – Gene Set Enrichment
6:00 pm – 7:00 pm – Dinner
Day 5 (Hands-on Bioinformatics & Ingenuity Pathway Analysis)
7:00 am – 9:00 am Self-Serve Breakfast
9:00 am – 10:45 am – Small Group Exercise Exploratory Analysis in R
10:45 am – 11:00 am – Break
11:00 am – 12:00 pm – Small Group Exercise Exploratory Analysis in R
12:00 pm – 1:00 pm – Lunch
1:00 pm – 3:00 pm Ingenuity Pathway Analysis
3:00 pm – 3:30 pm – Break
3:30 pm – 6:00 pm – Your
6:00 pm – 7:00 pm – Dinner (Dining Hall)
7:00 pm – 8:30 pm – Applied Bioinformatics Real World Examples
Day 6 (Machine Learning)
7:00 am – 9:00 am Self-Serve Breakfast
9:00 am – 10:00 am – Beyond What is Known – Machine Learning
10:00 am – 10:15 am – Break
10:15 am – 11:15 pm – Hands-on Machine Learning
11:15 am – 12:00 pm – Course Summary & Evaluations
12:00 pm – 1:00 pm – Lunch & Departure
On-campus housing is included in tuition.