RE: [R1b1c_U106-S21] OK, what measure(s) would be best for predicting ancestral U106 geography?
- Tom,Try population density unweighted by modern populations whose distribution is likely completed uncorrelated to populations thousands of years ago. If you are going to weight your data then scour the literature for estimates of early Bronze Age and late Neolithic populations of the various regions of Europe you want to compare.You could derive your population densities by equal land mass areas or if you want to take into count varying concentrations of people you could the areas of modern state/county/parish boundaries.I prefer to leave the data unweighted by modern assumptions as much as possible. I then leave it to the reader to draw their own conclusions based on their prefered assumptions/ theories about ancient population distributions, migrations, etc.I will be presenting my own analysis in the coming months once I am satisfied we have a large enough collection of SNP-confirmed haplotypes to make the sampling and selection bias errors negligible. Initially, I'd like to see 300+ haplotypes with European MDAs that can be pinpointed; with at least half from the continent. We're about half way there in the research group. This is still too small a number though. Ideally, we'll need 1000+ such haplotypes, which we may see within a couple of years. We need interest in genetic genealogy to pick up in continental Europe first I suspect.Cheers, David.
From: R1b1c_U106-S21@yahoogroups.com [mailto:R1b1c_U106-S21@yahoogroups.com] On Behalf Of phelpscan
Sent: June 30, 2008 10:08 PM
Subject: [R1b1c_U106-S21] OK, what measure(s) would be best for predicting ancestral U106 geography?
I've been watching individual U106/U198+ datapoints and also (where
given in a study) U106/U198+ as a percentage of (old) R1b1c. I
revisited the percentages tonight to try to turn them into U106/198+ vs
all people in a country, thinking that might be a better measure. I
then picked up the 2000 census populations for those countries from
MapViewer's sample dataset, and multiplied those by the U106/198+
percentages of the total in a country.
Which one or combination or different measure is most useful for giving
us insight into the potential origin and/or expansion of U106/U198+ ?