The Center for Informatics and Graff Library is offering the following course:
RNAseq analysis tools for the wet-lab biologist: Using open-source programming languages Linux, R, and Python
The course is offered in four parts from 9 to 11 am, on August 6, 10, 13, and 17, in Conference Room G112, Graff Library. Register for the course here. Please note that you will need to register for each of the four classes in the course separately.
COURSE DESCRIPTION
Using real-world examples from publicly available “big” datasets, the objective of this course is to teach participants how to evaluate, process, analyze, interpret, and report information generated in the lab. The tutorial begins with the basic overview and use of a command line interface, i.e. a way to directly tell your computer what you want it to do by writing your own commands. From there, users will be introduced to Linux, R, and Python; open-source programming languages that are used world-wide by the scientific community to address a variety of data analysis, statistical, and graphical needs. With this information, and using either a local or cloud-based computing resource, participants will step through a high-throughput data analysis pipeline from an RNA sequencing experiment, starting with data uploading and finishing with visualization of results.
LESSONS
- All about the shell: what is it, how do you get to it, and basic commands.
- Programming languages used in the course: introduction, syntax, basic commands.
- Computing environments and getting set up for the analysis.
- RNAseq – take a raw data file and convert it to analyzable data (data upload, pre-alignment quality check, alignment, quantify reads, normalization, visualizations).
- Statistical analysis and data visualizations.
INSTRUCTORS
Omar Khalid, PhD, ORIEN Informatics, Center for Informatics
John Kaddis, PhD, Diabetes and Cancer Discovery Science, Diabetes Metabolism Research Institute
Denis O’Meally, PhD, Center for Gene Therapy, Hematologic Malignancies and Stem Cell Transplantation Institute
Allen Mao, High Performance Research Computing Center, Center for Informatics