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      Plotting in R for Biologists

      Quickly get started making nice plots in R to show off your data.

      This course is a 3-hour quick start guide for making plots in R using ggplot and ComplexHeatmaps. This package includes the R code and example data I used in the videos, so you can follow along and play with the data yourself. 

      R is a great language for science, including statistics and making plots, and this course is designed to be accessible to people with no programming experience. 


      Here is the outline:

      Lesson 1: A quick start guide — From data to plot with a few magic words

      Lesson 2: Importing and downloading data — From Excel, text files, or publicly available data, this lesson covers how to get all of it into R and addresses a number of common problems with data formatting issues.

      Lesson 3: Interrogating your data — Getting quick summary statistics and navigating data frames.

      Lesson 4: Filtering and cleaning up data — Kicking out the data that annoys you and polishing up the rest

      Lesson 5: Tweaking everything in your plots — Everything from color schemes to fonts to grid lines and tick marks, this lesson will show you how to change just about anything in a plot. Especially useful for creating plots for publication.

      Lesson 6: Plot anything! — Quick guide to each plot type including which types of data fit into each one. 

      - Bar plots

      - Scatter plots

      - Box plots

      - Violin plots

      - Density plots

      - Dot-plots

      - Line-plots for time-course data

      - Venn diagrams

      Lesson 7: Multifaceted figures — Splitting up your data by some column into multiple plots arranged in rows, columns, or even tables.

      Lesson 8: Heatmaps -- How to create everything from simple heatmaps to adding different clustering and trees, partitions, and labels on the sides.


      UPDATE:

      Lesson 8: You may need to replace `source("https://bioconductor.org/biocLite.R")` with `biocLite("ComplexHeatmap")` if you are on R version 3.5+.

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      05/18

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