CLUMPHAP: A simple tool for performing haplotype-based association analysis
SEPTEMBER 26, 2008
In the September issue of Genetic Epidemiology (Volume 32 Issue 6) Jo Knight, Dave Curtis and Pak Sham published a paper entitled "CLUMPHAP: A simple tool for performing haplotype-based association analysis". They have developed a new statistical method with the aim of improving the chances of identifying genes that effect disorders such as Bipolar Disorder. Finding such genes will give researchers information that is vital for developing cures and /or treatments.
Genes involved in disease can be identified by comparing patterns in the DNA of collections of people affected with the disease against the patterns in the DNA of unaffected individuals. One type of pattern that researchers commonly look at is a haplotype; these are the strings of variation that come from each of the individuals parents, for each gene there is one haplotype from the mother and one from the father. There are often large numbers of haplotypes in large populations making statistical analysis inefficient. The method published by Jo Knight and colleagues groups similar haplotypes together to improve the efficiency of analysis. It is implemented in a new computer program called CLUMPHAP which is freely available and easy to use.
The paper describes how data was simulated and used to compare the new method against techniques that are normally used for this type of analysis. Dr Knight’s technique proved more powerful than some and just as powerful as others. Furthermore there is potential for greater improvement. Further development will involve exploring different ways to measure similarity between haplotypes, and implementing additional statistics so that continuous measures like hyperactivity can also be analysed.
As well as being used to identify genes in new samples this method can now be applied to samples that have already been collected and may identify genes that were previously overlooked. For further information contact Jo Knight (J.Knight@iop.kcl.ac.uk).
This research was funded by the Medical Research Council