The Dodecad Oracle v1

Here is a little fun tool that tests the Dodecad v3 admixture proportions of an individual against all the reference populations, but also against the best pairwise combinations of these populations.

You need to install R to use it, and then download the program and double click on the file DodecadOracleV1.RData that can be found within the rar file. You will then be faced with a command prompt where you can enter the following commands:

Examining which populations are available

Just enter

X[,1]

You will see a list of 227 populations. You can use these population IDs in the next section.

Which populations are closest to a particular population?

Enter:

DodecadOracle("British_D")
[,1] [,2]
[1,] "British_D" "0"
[2,] "British_Isles_D" "0.9798"
[3,] "Cornwall_1KG" "1.1533"
[4,] "Kent_1KG" "2.265"
[5,] "Irish_D" "3.7643"
[6,] "Dutch_D" "4.5354"
[7,] "Mixed_Germanic_D" "6.8971"
[8,] "Norwegian_D" "11.3111"
[9,] "Orkney_1KG" "12.4652"
[10,] "Orcadian" "12.8195"

If you want to find e.g., the top-30 populations, rather than just the top-10, enter:

DodecadOracle("British_D", k=30)

Which populations are closer to a particular individual?

Enter the admixture proportions of the individual (from the "Individual results" tab of the spreadsheet) as follows:

DodecadOracle(c(4.6, 16.7, 33.6, 0, 23.2, 0.4, 0.6, 1.6, 0.7, 14.1, 4.5, 0.2))
[,1] [,2]
[1,] "Ashkenazi_D" "3.7908"
[2,] "Ashkenazy_Jews" "4.1473"
[3,] "Morocco_Jews" "6.338"
[4,] "S_Italian_Sicilian_D" "12.5443"
[5,] "Sephardic_Jews" "13.5067"
[6,] "C_Italian_D" "14.4554"
[7,] "Sicilian_D" "14.7469"
[8,] "S_Italian_D" "15.748"
[9,] "Tuscan_X" "15.9981"
[10,] "O_Italian_D" "16.1474"

Once again, you can specify k=30, if you desire the 30 top matching populations instead of the default 10.

Mixed Mode

You use mixed mode by adding mixedmode=T in any of the commands. The program then considers all pairs of populations, and for each one of them calculates the minimum distance to the sample in consideration, and the admixture proportions that produce it; population pairs where the distance to one of the two populations is smaller than to any admixture of the two are ignored.

Example:

DodecadOracle("Pathan",mixedmode=T)
[,1] [,2]
[1,] "Pathan" "0"
[2,] "84.8% Pakistani + 15.2% Urkarah" "1.075"
[3,] "84% Pakistani + 16% Stalskoe" "1.1555"
[4,] "63.9% TN_Brahmin + 36.1% Urkarah" "1.6669"
[5,] "32.4% Urkarah + 67.6% Meghawal" "2.3516"
[6,] "56.3% INS + 43.7% Urkarah" "2.4901"
[7,] "11.5% Adygei + 88.5% Pakistani" "2.6245"
[8,] "82.4% Sindhi + 17.6% Stalskoe" "2.6318"
[9,] "62.9% AP_Brahmin + 37.1% Urkarah" "2.7322"
[10,] "11.2% Lezgins + 88.8% Pakistani" "2.7749"

The mixed mode should be used with caution, and it shows, more than anything else, how similar apparent "mixes" can be achieved by different combinations of ancestry. Nonetheless, it may prove somewhat useful. For example, there is a suggestion in the above results, that Pathans can be viewed as a mix of other South Asian populations and populations from the eastern Caucasus, a suggestion that was arrived at independently by the Project using different methods.

Here is another example:

DodecadOracle("Assyrian_D",mixedmode=T)

[,1] [,2]

[1,] "Assyrian_D" "0"

[2,] "83.9% Armenians_16 + 16.1% Yemen_Jews" "1.7829"

[3,] "89.1% Armenian_D + 10.9% Saudis" "2.1624"

[4,] "84.3% Armenians_16 + 15.7% Saudis" "2.2884"

[5,] "88.9% Armenian_D + 11.1% Yemen_Jews" "2.2983"

[6,] "83.8% Armenian_D + 16.2% Bedouin" "4.1579"

[7,] "72.2% Armenian_D + 27.8% Syrians" "4.1841"

[8,] "23.4% Georgians + 76.6% Iraq_Jews" "4.2418"

[9,] "76.2% Armenians_16 + 23.8% Bedouin" "4.332"

[10,] "61.5% Armenians_16 + 38.5% Syrians" "4.4019"

This reaffirms the close relationship of Assyrians to Armenians that has been noticed in the project and by others, and it also shows that Assyrians differ from Armenians in a Southwestern Asian direction, consistent with their Semitic language.

Or, African Americans:

DodecadOracle("ASW",mixedmode=T)

[,1] [,2]

[1,] "ASW" "0"

[2,] "81.3% Hausa + 18.7% N._European" "2.3891"

[3,] "18.4% Orkney_1KG + 81.6% Hausa" "2.4031"

[4,] "18.5% Argyll_1KG + 81.5% Hausa" "2.4268"

[5,] "18.4% Orcadian + 81.6% Hausa" "2.4657"

[6,] "80.5% Igbo + 19.5% N._European" "2.5031"

[7,] "80.6% Brong + 19.4% N._European" "2.523"

[8,] "18.6% CEU + 81.4% Hausa" "2.5938"

[9,] "19.1% Argyll_1KG + 80.9% Brong" "2.6197"

[10,] "19% Orkney_1KG + 81% Brong" "2.6274"

I don't know that much about the slave trade, but I believe that Ghana was an important part of it?

Another thing to watch, is that some populations tend to have more than one sample available, so they appear to be mixtures of themselves, which is not really very informative, e.g., Spanish_D

DodecadOracle("Spanish_D",mixedmode=T)

[,1] [,2]

[1,] "Spanish_D" "0"

[2,] "7.9% French_Basque + 92.1% IBS" "0.8713"

[3,] "68.9% IBS + 31.1% Spaniards" "1.0377"

[4,] "98.8% IBS + 1.2% Irish_D" "1.2959"

[5,] "1.2% British_Isles_D + 98.8% IBS" "1.3018"

[6,] "1.2% British_D + 98.8% IBS" "1.3019"

[7,] "99% IBS + 1% Norwegian_D" "1.3046"

[8,] "1.2% Cornwall_1KG + 98.8% IBS" "1.3048"

[9,] "98.8% IBS + 1.2% Kent_1KG" "1.3142"

[10,] "2.2% French_D + 97.8% IBS" "1.3179"

To deal with these problems, you must "edit" the X matrix if you want to exclude some populations. For example, if you want to exclude "Spaniards" and "IBS", you must enter:

X <- X[setdiff(1:227,which(X[,1]=="IBS" | X[,1]=="Spaniards")),]

but notice, that you must relaunch the program, if you want to get the original matrix, or alternatively save it like this:

Z<-X

and then retrieve it like this:

X<-Z