Today I am releasing new versions of about half my association software. It’s been a while since I released new versions of any of these tools, and in the mean time they’ve been more and more integrated making it harder to release them independently. Now, since we needed to use them all up in Iceland last we visited DeCODE — myself in December and three other from my group in January — we needed to get all the software synchronized anyway, so I wanted to take that opportunity to make a major release.
I had planned to make the release close to New Year, so I code-named it the New Year release. I think I should re-name it to the Chinese New Year release. That is close enough that I can defend it.
Of course, it is even closer to the next planned release — the Happy Birthday release — that was supposed to come out tomorrow (at my birthday, of course). That release is likely to be delayed a couple more weeks, though, but I am sticking to the code name.
By the way, you can see the road-map for that here.
The software release consists of the following:
SNPFile — a library and API for manipulating large SNP datasets with associated meta-data, such as marker names, marker locations, individuals’ phenotypes, etc. in an I/O efficient binary file format. Version 2.0 adds a completely new serialization framework for storing meta-data. The previous one — based on Boost serialization — wasn’t binary compatible across platforms, the new one is. We also add a Python module for manipulation of SNPFiles, version 1.0 of that.
SMA — tools for single marker association tests. Currently there are three tools, two for case/control data and one for quantitative traits. Version 1.2 extends the tools with options for doing both genotype and allelic (additive) tests.
Blossoc — BLOck aSSOCiation. Blossoc is a linkage disequilibrium association mapping tool that attempts to build (perfect) genealogies for each site in the input and score these according to non-random clustering of affected individuals, and judge high-scoring areas as likely candidates for containing disease affecting variation. Building the local genealogy trees is based on a number of heuristics that are not guaranteed to build true trees, but have the advantage of more sophisticated methods of being extremely fast. Blossoc can therefore handle much larger datasets than more sophisticated tools, but at the cost of sacrificing some accuracy. Version 1.3 adds methods for scanning for quantitative traits and is tightly integrated with SNPFile.
HapCluster — a Bayesian Markov-chain Monte Carlo (MCMC) method for fine-scale linkage-disequilibrium mapping, described in details in:
Fine Mapping of Disease Genes via Haplotype Clustering. E.R.B. Waldron, J.C. Whitaker and D.J. Balding. Genetic Epidemiology. 30: 170–179. (2006)
a tool I develop in collaboration with David Balding’s group at Imperial College London. Version 2.2 is basically just integration with SNPFile 2.0. The next major development of HapCluster is what I have planned for the Happy Birthday release.