In this tutorial you will learn: what is a heatmap how to create a clean, highly customizable heatmap using heatmap.2 in the gplots package in R how to remove samples with poor output (not very many sequences) how to rearrange your samples by a metadata category how to make a color coded bar above the heatmap 
So you’ve finally managed to install the pesky environment but have no idea what you are looking at when you open the program. This tutorial is for you. (Again, here is a version with screenshot pictures). When you open R, it might look different than the screenshots in the picture version of the tutorial. This 
Scatterplot matrices are a great way to roughly determine if you have a linear correlation between multiple variables. This is particularly helpful in pinpointing specific variables that might have similar correlations to your genomic or proteomic data. If you already have data with multiple variables, load it up as described here. If not, no worries 
Have no fear, the screenshots are here! (For the original tutorial, click here) Method 1 (less typing) Part 1-Getting the Package onto Your Computer Open R via your preferred method (icon on desktop, Start Menu, dock, etc.) Click “Packages” in the top menu then click “Install package(s)”. Choose a mirror that is closest to your geographical location. Now 
Today we are going to make additions to our R environment in a common process called installing packages. The transition won’t be as long, drastic nor emotional as an episode of Extreme Makeover: Home Edition, but it does add on more capabilities to your R environment. A package is a bunch of codes combined and distributed 
Feeling faint of heart without photos depicting what to do? No worries, here they are. Go to the R website and click “Download R” under “Getting Started” Choose a place to download R. Even though we’re on the limitless and borderless interweb, choosing a location close to you helps speeds things up. Choose which R package to download based 
I will make a confession. This past summer, I didn’t spend my spare time watching relentlessly addicting TV shows nor clubbing in San Francisco. Instead, I checked out figures. No, not the sort of figures you’re probably thinking about. The ones that are included in research papers and have the potential to be beautiful works of 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
