I’m excited to announce that I’ve updated the R package qtlbim. I forked the code from the CRAN Github repo for qtlbim. Here is the updated qtlbim repository in my Github account. It now works smoothly with gcc10, thanks to patches from Dirk Eddelbuettel.
Installation
To install qtlbim from my Github repository, type this code:
remotes::install_github("fboehm/qtlbim")Getting started with Bayesian QTL mapping
Once you’ve installed qtlbim, browse the vignettes to find example analyses.
Why qtlbim is cool
qtlbim uses a Bayesian framework to model genetic architectures of complex traits in
two-parent crosses. It allows traits to have multiple quantitative trait loci (QTL) across the genome.
qtlbim uses a Markov chain Monte Carlo (MCMC) strategy to obtain samples from the
posterior distribution. It then summarizes those samples for inference purposes.
MCMC sampling code is written in C, so it’s lightning fast. The algorithms are also efficiently written, as discussed in the journal articles from Yi, et al. and Yandell, et al.
History
The amazing Brian Yandell and Nengjun Yi and collaborators developed qtlbim starting in the mid 2000s. It was on CRAN as recently as 2013.
Plans
I will continue to add documentation to the package. Vignettes may be updated. They are currently written as Rnw files. Because the package development preceded widespread use of Roxygen2, devtools, and rmarkdown R packages,
it may be some work to modernize the documentation.
Unit tests and continuous integration will also be added. Following more substantive updates, I’ll incorporate a qtlbim webpage into my site.
I welcome feature requests via my Github repository.
(Last modified: 2021-02-15 19:47:57.666052668-05:00[America/New_York])