If you would like to participate please contact us. Donations to the general fund to support those who cannot afford the cost of the test are welcome.
Everytime you buy from Amazon, please click on the link shown to the left and the Hawgood family DNA study will receive a small fee which will fund more tests.
Put simply, if the markers all match then those tested are very closely related. If a marker does not match, this is known as a mutation, and the more mutations that exist, the further apart those being tested.
As a rule of thumb, in the Genebase test of 44 different markers, there is a 0.4% chance of any one of the 44 mutating, which means that there is, statistically, the expectation of just one mutation on one of the 44 markers every 250 years for each person tested. In a 67 marker test, there would be on average a mutation every 100 years. For those mathematically minded, the extra 23 markers are faster mutating markers, which proportionally brings down the average time period for a mutation.
Using the number of mutations and the average expected mutation rate, we can calculate the statistically likely generation gap between 2 parties being tested. But a word of caution on the maths - and more on this later. The calculation to the most recent ancestor rests on the average mutation rate and there is a great deal of debate and confusion on this topic. Early studies (Walsh 2001) indicated a rate of 0.0020, or 0.2% per marker, but later studies has shown mutation rates of 0.0040, or 0.4% per marker. Some more recent data indicates rates in excess of 0.5% per marker.
The existence of more recent higher mutation rates is very easy to explain. Walsh studied only slow mutating markers, and the results were valid for these markers. More recent studies have used many more markers than Walsh, and these markers have higher mutation rates, which raises the average.
Between testing companies, the average mutation rates will also vary as different markers are tested. Using accurate mutation rates is key as if the wrong ones are used, for example applying Walsh 0.2% rates to a set of markers which includes faster mutating markers, the estimate of the most common recent ancestor will be wildly out.