Averages and ranges can be found here. For a multiple cousin relationship predictor, click here. For original, unweighted relationship probabilities, click here. You would want to use the unweighted predictor if you believe you know how a match fits into your family tree. You would want to stay on the current page if you don't know who your match is. Population weights give a significant advantage to more distant cousins because a person likely has about 5x as many 2nd cousins as 1st cousins a perhaps almost 100,000x as many 8th cousins. Population weights here are only applied to 1st cousins and more distant. You probably have a better idea of the likelihood that you have a very close unknown relative than any population weighting schema would.
1C1R = 1st cousin, once removed; cM = centiMorgan, HIR = half-identical regions; IBD = identical by descent (HIR + FIR).
All probabilities are for autosomal DNA only. Please subtract any X-DNA before using the calculator. Also, I recommend subtracting any shared DNA from segments less than 7 cM that may have found their way into your total.
The above probabilities assume no endogamy or other pedigree collapse. Those cases should be treated separately.
Parent/child relationships are not included here. They are easy to distinguish from other relationships, including full-siblings. Parent/child relationships consist of a half-identical match across the whole length of the genome. Full-siblings share 25% fully-identical regions (FIR), on average. Genotyping sites will take this into account in their relationship prediction. If a relationship is predicted to be parent/child, full-sibling is not a possible relationship and there is no need to analyze the shared DNA amount here.
Relationships more distant than 1C1R and half-1C are grouped together by those with the same average shared DNA. Also, half-aunt/uncle/niece/nephew relationships are treated the same as siblings of grandparents, which are called great- or grand-aunts/uncles/nieces/nephews. They are treated the same because the curves are the same, as are any other relationship types that share the same curve. For each curve shown in the figure at the bottom of the page, 500,000 pairs were simulated. Additional weight is then given to more distant relationships. Age and other factors, such as the likelihood that your unknown great-grandparent or great-grandchild is the DNA match you've found, should be taken into consideration. It's probably more likely that a 1,200 cM match is a half-aunt/uncle/niece/nephew than a great-grandparent, despite the fact that, if they were equally likely relatives to find as DNA matches, the cM value alone suggests great-grandparent is much more likely.
These probabilities are calculated as far back as 8C. For distant relatives, there's much less certainty about the genealogical relationship for your DNA matches. Matches as low as 8 cM are allowed here, however the relationship may be farther back than 8C. While the relative probabilities are accurate for the relationship types shown, one also has to consider that the relationship is farther back. Indeed, any of the probabilities shown above are only relative to the other relationships listed and are therefore only meaningful in comparison to the other relationships. Not only are very low cM values difficult to assign to a recent ancestor, but segments of 20 cM or 30 cM may be on pile-up regions and therefore come from very distant ancestors.
Totals will not always add up to 100%. When more relationship types are possible, the chance of rounding errors increases. I don’t believe that the totals are ever off by more than 0.2 percentage points. For more information about the methodology and discoveries associated with this tool, click here.
This is not the first tool to show relationship probabilities based on a user input of shared DNA. Jonny Perl has done amazing work at DNA Painter, including probability calculations that can be built in to your family tree, and Genetic Affairs also displays relationship probabilities.
One huge advantage of this tool, other than the accuracy of the data, is that it treats close relatives as not being in the same group because the curves are significantly different, as can be seen in the graph below.