R/qtl2 QTL analysis for high-dimensional data and complex crosses
- qtl2geno, for calculating genotype probabilities, imputations, and genetic maps
- qtl2scan, for QTL genome scans and related calculations
- qtl2plot, for data visualization
- qtl2convert, for converting data among the R/qtl2, DOQTL, and R/qtl formats
- qtl2db, for connecting to genome databases
In R/qtl2 version 0.5, we made major revisions to some of the
central data structures, and a number of steps in QTL analyses have
changed. See the revised
user guide, or
this description of the changes in version 0.5.
A couple of functions for converting objects from the format for
Rqtl2 version 0.4 and the new format are in
For discussion/questions about R/qtl2, join the rqtl2-disc google group. Or join rqtl-announce for announcements about R/qtl and R/qtl2. (We’ll try to keep the original rqtl-disc group for the discussion/questions about the original R/qtl only.)
First, make sure you have the latest version of R (3.4.2).
The qtl2 package is inspired by the tidyverse package; it is basically empty, but when you install it, the qtl2geno, qtl2scan, qtl2plot, and qtl2convert packages, plus a bunch of dependencies, will be installed.
Alternatively, you can install R/qtl2 from its source on GitHub. (But note that compiling the C++ code can be rather slow.)
On Windows, you’ll need Rtools.
You then need to install the devtools package, plus a set of package dependencies: yaml, jsonlite, data.table, RcppEigen, RSQLite, and qtl. (Additional, secondary dependencies will also be installed.)
install.packages(c("devtools", "yaml", "jsonlite", "data.table", "RcppEigen", "RSQLite", "qtl"))
Finally, install R/qtl2 using
- user guide
- input file formats (also see the sample data files and the qtl2data repository)
- preparing DO mouse data for R/qtl2
- differences between R/qtl and R/qtl2
- developer guide
- HMM benchmarks
- linear regression benchmarks
The qtl2geno, qtl2scan, qtl2plot, and qtl2convert packages are free software; you can redistribute them and/or modify them under the terms of the GNU General Public License, version 3, as published by the Free Software Foundation.
These programs are distributed in the hope that they will be useful, but without any warranty; without even the implied warranty of merchantability or fitness for a particular purpose. See the GNU General Public License for more details.
A copy of the GNU General Public License, version 3, is available at https://www.r-project.org/Licenses/GPL-3
Sources on github: