Stat7350: Analysis and Visualization of Biological Data

Offered Winter 2019, The University of Manitoba

This course would not have been possible without access to materials from others who have developed and taught similar lessons and graciously shared their material online. 

Week 1: Git & Github
LESSON:
  • Integrate RStudio and git: Jenny Bryan Happy Git with R (link) 
  • DataCamp: "Basic Workflow"

Weeks 2 & 3a: Introduction to ggplot and visualization of graphics
LESSONS:
  • Session 1  (rmd) (pdf)
  • Session 2  (rmd) (pdf)
  • Session 3  (rmd) (pdf)
    • ​​​#TidyTuesday Compiled Figures (pdf)
Data from: esapubs.org/archive/ecol/E090/118/ vis datacarpentry.org/ecology-workshop/data/
FOLLOW-UP READING:
  • Fundamentals of Data Visualization (link)
SOURCE MATERIAL:
  • Jenny Bryan, UBC Stat 545 (link)
  • Data Carpentry Ecology workshop (link)
  • ggmosaic package vignette (link)
  • geom_bar discussion (link)

Week 3b: Tidy Data
LESSON: FOLLOW-UP:
  • DataCamp ("Working with data in the Tidyverse")
SOURCES:
  • Jeb Byrnes, Intro to Data Science for Biology (link)
  • Amelia McNamara RStudio::Conf2019 workshop (link)
  • Thomas Girke, Data Analysis in Genome Biology (link) 
  • Modern Dive (link)

Week 4 & 5: Experimental design 
LESSON:
  • Session 5 (Rpres)
  • Session 6 (rmd) (pdf)
  • Session 7 (rmd) (pdf)
FOLLOW-UP READING:
  • Why Most Published Research Findings Are False (pdf)
  • Big data: are we making a big mistake? (pdf)
SOURCES:
  • ***Whitlock & Schluter,  The Analysis of Biological Data, 2nd Ed (data link)
  • ***Karl Broman, UWM Statistics for laboratory scientists I (link) 
  • ***Dolph Schluter, UBC Biology 501 (link)

  • Solveig Mjelstad Olafsrud, Introduction to Microarray technology course (pdf)
  • Jim Deacon, Biology Teaching Organisation, University of Edinburgh (link)
  • Jeff Leek, Statistics for Genomic Data Science (link)

Assignments
  • Assignment 1: Data visualization (pdf)
  • Assignment 2: Experimental design (pdf)
  • Assignment 3: Data analysis & communication (pdf)
    • Link to data set (csv)