This short course teaches you to analyze and visualize large, complex biological data sets use the R statistical programming language, RStudio, and new tools available in the “tidyverse”. We use common biological experiments to illustrate analysis strategies including studies of mRNA expression, histone post-translational modification in the context of chromatin, and cell-type characterization using single cell approaches.
IDPT 7810 006
The course (2 credit hours) consists of 13 2 hour classes held Mon through Fri from Nov 28 through Dec 14 in P28-1202 (P28-2301 on Dec 6, 7, and 12) from 1:00-3:00 pm. Building P28 is Education 2 North.
We have dedicated office hours on Thurs from 2:30-4pm in RC1 South 9th
floor in the main office (behind the glass walls). Come with questions,
problems, etc. Please send an email to [email protected] to let
us know you’re coming.
Jay Hesselberth ([email protected])
Austin Gillen ([email protected])
Kent Riemondy ([email protected])
Rui Fu ([email protected])
You can install the course package from github with:
# install.packages("devtools")
devtools::install_github("idpt7810/practical-data-analysis")