Epistasis Blog

From the Computational Genetics Laboratory at Dartmouth Medical School (www.epistasis.org)

Friday, December 30, 2005

2006 BioGEC Workshop

I am organizing (with Marylyn Ritchie) the 2006 Workshop on the Biological Applications of Genetic and Evolutionary Computation (BioGEC'06). This workshop will be held as part of the 2006 Genetic and Evolutionary Computation Conference (GECCO-2006) in Seattle. The call for papers can be found here. Let me know if you are interested in participating or have any questions.

Important Dates
March 31, 2006: papers due
April 5, 2006: acceptance notices
April 19, 2006: camera ready revisions due
July 8 or 9, 2006: BioGEC workshop

Monday, December 26, 2005

Wikipedia entry for MDR

I have added a brief description of our multifactor dimensionality reduction (MDR) approach to Wikipedia, the free encyclopedia. You can access the entry here.

Sunday, December 18, 2005

Open-Source MDR 0.6.2

The Dartmouth CGL is pleased to announce the release of version 0.6.2 BETA of our open-source multifactor dimensionality reduction (MDR) software package. The new version can be downloaded from Sourceforge.net by clicking here. The new version is able to model datasets that have more of one class than the other (e.g. more controls than cases). MDR models interactions in imbalanced datasets using 'balanced accuracy' in combination with a threshold for assigning risk that is equal to the ratio of class 1 (e.g. cases) to class 0 (e.g. controls) in the data. The use of balanced accuracy replaces the old metric based on just accuracy. Here, balanced accuracy is the arithmetic mean of sensitivity and specificity or (sensitivity+specificity)/2. We have a paper that is in prepration that shows using simulated data that balanced accuracy is superior to accuracy when the data are imbalanced. Of course, when the data are balanced, the two metrics are identical. The MDR permutation testing module has also been updated to version 0.4.5.

The next release of open-source MDR will include new graphical output to facilitate the statistical interpretation of MDR models. A future version will also include the interactive ability to construct attributes using the MDR algorithm for inclusion in the dataset and reanalysis. Our paper that is 'in press' in the Journal of Theoretical Biology (see post from Nov. 30, 2005) describes some of the ideas behind these new features.

We hope to have MDR 1.0 ready by the end of Feb. Please send us your comments, suggestions, and criticisms on the BETA version before then.

MDR C Library

The Dartmouth CGL is please to announce the release of a C library for implementing the kernel of the multifactor dimensionality reduction (MDR) algorithm that carries out constructive induction (CI). We think this new C library will be useful for those wanting to incorporate MDR into a high-performance data mining application written in C or C++. The code is optimized with a new CI algorithm for fast MDR analysis. The beta version of libMDR can be downloaded from Sourceforge.net by clicking here.