Sunday, September 17, 2017
Ancient IBD/cM matrix analysis offer
I've had a few requests from personal genomics customers to stick their files into an Identity-by-Descent/cM matrix like the one at the link below. Also please check out the accompanying comments thread for ideas of what can be done with the output. A Bronze Age dominion from the Atlantic to the Altai I can do this for $15 (USD) per individual.
Please e-mail the data and money (via PayPal) to eurogenesblog [at] gmail [dot] com. The deadline for sending through the data files (which, in this run, can only be from 23andMe, Ancestry or FTDNA) is this time Tuesday.
I'll send out the results to each participant over e-mail. However, participants are encouraged to post their results in the comments thread at my other blog here, so that they can be discussed and analyzed further.
Update 20/09/2017: The analysis is underway. Please don't send any more data files. If there's enough interest, I'll do another run soon.
Update 22/09/2017: I've just sent out the results to the participants in the form of two text files titled "ancients_only" and "full_column". The former is a matrix of overall shared haplotype tracts in centimorgans (cM) that includes the user and 65 ancient genomes, and the latter a list of haplotype tracts, also in cM, shared between the user and well over 3000 public samples.
So what can we do with these files? For one, we can look at them, because simply eyeballing these sorts of stats can be very informative. Sorting the data in some way and calculating population averages might help with that.
The "ancients_only" file can be used for slightly more advanced analyses. For instance, below is a Neighbor joining graph produced with the Past 3 program (freely available here). I simply loaded my "ancients_only" file into Past 3, selected all of the columns and rows, and then did this: Multivariate > Clustering > Neighbor joining. Note that I cluster on the same branch as Slav_Bohemia, and this makes perfect sense considering my Polish ancestry. By the way, I dropped Oetzi from this run because he was behaving strangely, which is not unusual for low coverage genomes. Click on the image and open in a new tab for a better view.
here and combined, in part or in whole, with your other files so that you can analyze yourself alongside a larger number of individuals.