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PLINK/SEQ is an open source C/C++ library for analyzing large-scale genome sequencing data. The library can be accessed via the pseq command line tool, or through an R interface. The project is developed independently of PLINK but it's syntax will be f... [Read more...]

Last year I showed you how to create manhattan plots, and later how to highlight regions of interest, using ggplot2 in R. The code was slow, required a lot of memory, and was difficult to maintain and modify. I finally found time to rewrite the code u... [Read more...]

I'm working on a project using next-gen sequencing to fine-map a genetic association in a gene region. Now that I've sequenced the region in a small sample, I'm picking SNPs to genotype in a larger sample. When designing the genotyping assay the lab wi... [Read more...]

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The *ABEL suite of R packages and software for genetic analysis has grown substantially since the appearance of GenABEL and the previously mentioned ProbABEL R packages. There are now a handful of useful R packages and other software utilities facilita... [Read more...]

A few months ago I covered an algorithm called EMMA (Efficient Mixed-Model Association) implemented in R for simultaneously correct for both population stratification and relatedness in an association study. This method/software is very useful because ... [Read more...]

A few weeks ago I covered an R package for efficient mixed model regression that is capable of simultaneously accounting for both population stratification and relatedness to compute unbiased estimates of standard errors and p-values for genetic associ... [Read more...]

I recently did an analysis for the eMERGE network where I had lots of individuals from a small town in central Wisconsin where many of the subjects were related to one another. The subjects could not be treated as independent, but I could not use a fam... [Read more...]

I've been using GenABEL for some time now for GWAS analysis using related individuals. It has an excellent set of functions for estimating a kinship matrix from a dense marker panel and then using this in a linear mixed effects model to allow for relat... [Read more...]

A few months ago I showed you in this post how to use some code I wrote to produce manhattan plots in R using ggplot2. The qqman() function I described in the previous post actually calls another function, manhattan(), which has a few options you can s... [Read more...]

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... [Read more...]

Update Friday, May 14, 2010: See this newer post on LocusZoom. If you caught Cristen Willer's seminar here a few weeks ago you saw several beautiful figures in the style of a manhattan plot, but zoomed in around a region of interest, with several ot... [Read more...]

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 ... [Read more...]

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. ... [Read more...]

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 ... [Read more...]