Current Version 1.3.4 (May 21, 2013)

[ Installation | Status | Screen shots ]

J/qtl is a Java graphical user interface (GUI) for the popular QTL data analysis software R/qtl. It provides a flexible and powerful working environment for users to perform a variety of tasks.

How it works

J/qtl is a graphical user interface (GUI) for R/qtl, which is an add-on package for the freely available statistical language R. While R/qtl is a powerful data analysis software package, it requires some programming skills. We developed J/qtl to help people without programming skills to analyze their data. The software works in such a way that people do their job through the point and click interface. The software translates the users' actions into R commands, runs the commands in R, and displays the results. So R/qtl is performing most of the analysis and J/qtl is providing a user friendly interface. J/qtl uses the third party Java/R Interface (JRI) software package to integrate with R.

What is R and why R

R is a programming language and environment for statistical computing. It provides a wide variety of statistical functions and is highly extensible. Also R is open source and free of charge. The syntax used by R is very similar to S (and Splus).

Given the rich collections of statistical tools provided by R, rewriting them would be a waste of resources. We therefore decided to utilize them and make the development easier.

Why R/qtl

R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. Among numerous QTL analysis software, R/qtl implements the most comprehensive set of methods. Computationally intensive parts were written in C for better performance.

The current version of R/qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). The fit of higher-order QTL models may be fit by multiple imputation.

Why Java

Java offers platform independence and a rich collection of GUI components which allow us to make J/qtl's interface look nice and highly interactive.


The software and manual were written by Hao Wu, Lei Wu and Keith Sheppard. Some Java code was borrowed from TIGR's MultiExperiment Viewer (TMEV) software.

Help and Contact Information

Help on using J/qtl is integrated into the J/qtl application. After installation you can use the help menu item to view all help topics or you can use context sensitive help which are included in all application dialogs.

We are eager to hear about your problems/questions/suggestions. To contact the J/qtl group please send email to jqtl@jax.org.