The mission of the GenABEL project is to provide a free framework for collaborative, robust, transparent, open-source based development of statistical genomics methodology. We aim to streamline methodology discussion, development, implementation, dissemination and maintenance; through the community.Follow us on [ Twitter ] [ Facebook ] READ MORE
GenABEL development has made a big step forward with the use of the Jenkins continuous integration platform. Our Jenkins server automatically runs a series of checks each time a change in the code is committed to our SVN version control system. This enables us to continuously monitor the health of our code base by running static code analysis, checks for memory leaks, adherence to coding standards, etc. Hopefully this increases both the stability and the maintainability of the code.
(To continue reading this story click on 'read more' below.)
Shortly after the introduction of ProbABEL v0.4.0 a small bug was discovered when running with the
--mmscore option. This release fixes that bug. The source code and more information can be found on the ProbABEL page.
The ProbABEL development teams is happy to announce the release of ProbABEL v0.4.0.
The most important user-visible changes are:
1) the output files now contain a column with chi2 values.
2) the CoxPH module is now fully functional again and can use filevector (DatABEL) files as well
3) for those of you who use
probabel.pl: the way the -o option works has been slightly changed.
Thanks to all who made this release possible, by providing code, by being beta testers, by suggesting enhancements, or otherwise.
(Please click on "read more", below, for more details.)
A new mailing list (genabel-announce for short) has been created so we can more easily inform our users of new versions of existing packages as well as of new packages that have been added to the GenABEL project.
Last week (July 10, 2013), Yurii Aulchenko presented the GenABEL project at the UseR!-2013 conference at Albacete, Spain. Short report and highlights are available from Yurii's blog. The presentation and its source is available on our web-site (section Showcase/Presentations).
The team led by Prof. Axenovich has published the manuscript on "Region-Based Association Analysis of Human Quantitative Traits in Related Individuals". Additionally to providing a region-based analysis method, the manuscript also features description of the GRAMMAR+ transformation, which allows treating transformed trait values as if they were measured in a population-based study of unrelated individuals. [click on 'READ MORE' below for complete story]
We are glad and proud to announce that the open source GenABEL project became even more open with the release of the source of the "GenABEL tutorial". The source material is released under the CC-BY-SA 3.0 license. Everybody is invited to copy, modify, extend, and share the source further.
The OmicABEL (pronounced as "amicable") package allows rapid mixed-model based genome-wide association analysis, especially for multiple traits ("omics" data).
The GenABEL suite, while originally designed for the analysis of human genomic data, is also widely used for analysis of animal and plant data.