If you attended Frank Harrell's Regression Modeling Strategies course a few weeks ago, you got a chance to see the rms package for R in action. Frank's rms package does regression modeling, testing, estimation, validation, graphics, prediction, and ty...
Posts Tagged ‘ Tutorials ’
Frank Harrell’s Regression Modeling Strategies Course Handouts
The previously mentioned Regression Modeling Strategies short course taught by Frank Harrell is nearly over. Here are the handouts (PDF) from the course. Keep an eye out here, I'll be writing a few more posts in the near future on topics Frank covered...
Happy Birthday GGD! The 10 Most Popular Posts Since GGD’s Launch
The first post on Getting Genetics Done was one year ago today. To celebrate, here are the top 10 most viewed posts since GGD launched last year. Incidentally, nine of the ten are tutorials on how to do something in R. Thanks to all the readers and all...
GWAS Manhattan plots and QQ plots using ggplot2 in R
Will posted earlier this week about how to produce manhattan plots of GWAS results using Stata, so I thought I'd share how I do this in R using ggplot2. First, if you've never used ggplot2, you'll need to add it to your R installation by typing: install.packages("ggplot2") Once you've done that, copy and paste this command to download the functions I wrote...
Coming to R from SQL, Python, SAS, Matlab, or Lisp
Head over to Revolutions Blog for a list of PDF and powerpoint resources for making the transition to R from other programming or stats languages. All of these notes come from the New York R meetup. I enjoyed browsing the meetup's files - lots of powerpoints, PDFs, and example R data files for various topics, including several slideshows on...
ggplot2 Tutorial: Scatterplots in a Series of Small Multiples
It took several months after learning about ggplot2 before I gave it a try myself. I was apprehensive about learning a new graphics system with a new set of commands. Thing is, if you've ever used plot() in R, you already know how to use much of the functionality in ggplot2! In this tutorial I want to show you...
R examine objects tutorial
This article is quick concrete example of how to use the techniques from Survive R to lower the steepness of The R Project for Statistical Computing‘s learning curve (so an apology to all readers who are not interested in R). What follows is for people who already use R and want to achieve more control Related posts:
QQ plots of p-values in R using ggplot2
Way back will wrote on this topic. See his previous post for Stata code for doing this. Unfortunately the R package that was used to create QQ-plots here has been removed from CRAN, so I wrote my own using ggplot2 and some code I received from Daniel Shriner at NHGRI. Of course you can use R's built-in qqplot() function, but...
Split, apply, and combine in R using PLYR
While flirting around with previously mentioned ggplot2 I came across an incredibly useful set of functions in the plyr package, made by Hadley Wickham, the same guy behind ggplot2. If you've ever used MySQL before, think of "GROUP BY", but here you can arbitrarily apply any R function to splits of the data, or write one yourself. Imagine you have...
Visualizing sample relatedness in a GWAS using PLINK and R
Strict quality control procedures are extremely important for any genome-wide association study. One of the first steps you should take when running QC on your GWAS is to look for related samples in your dataset. This does two things for you. First, you can get an idea of how many related samples you have in your dataset, and second,...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
