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Caratacus
02-03-2016, 01:06 PM
Instead of using the GEDmatch Oracle facility to find the proximity between an individual and populations, I want to use it for population : populations. How do I do this?

I am especially interested in using the Eurogenes K13 Oracle for these populations:

Southeast English
Irish
Danish
Tuscan

Mestace
02-03-2016, 04:35 PM
Instead of using the GEDmatch Oracle facility to find the proximity between an individual and populations, I want to use it for population : populations. How do I do this?

I am especially interested in using the Eurogenes K13 Oracle for these populations:

Southeast English
Irish
Danish
Tuscan


You need to get the DIY version of the calculator, the spreadsheet and a working file to use in 4mix. Then increase the number of populations listed in Oracle (20 might not cut it to get them all) then input the averages.

For example Tuscans that i already ve done some time ago :


Least-squares method.

Using 1 population approximation:
1 Tuscan @ 0,56439
2 North_Italian @ 7,67412
3 West_Sicilian @ 8,30601
4 Italian_Abruzzo @ 9,368907
5 Greek_Thessaly @ 11,427996
6 Central_Greek @ 13,453789
7 East_Sicilian @ 13,60797
8 South_Italian @ 14,898894
9 Ashkenazi @ 16,800847
10 Spanish_Extremadura @ 16,848757
11 Portuguese @ 17,123889
12 Bulgarian @ 17,356699
13 Spanish_Andalucia @ 17,716192
14 Romanian @ 17,937989
15 Spanish_Murcia @ 17,981891
16 Spanish_Valencia @ 18,574847
17 Spanish_Galicia @ 18,756684
18 Spanish_Castilla_Y_Leon @ 19,557642
19 Spanish_Cataluna @ 19,56122
20 Italian_Jewish @ 20,081383
21 Spanish_Castilla_La_Mancha @ 20,112012
22 Sephardic_Jewish @ 20,29644
23 Algerian_Jewish @ 20,904528
24 Serbian @ 21,260033
25 Spanish_Cantabria @ 22,504045
26 Spanish_Aragon @ 23,052667
27 French @ 23,112539
28 Southwest_French @ 24,450292
29 Tunisian_Jewish @ 25,246438
30 Libyan_Jewish @ 25,602658
31 West_German @ 27,69843
32 Algerian @ 28,394535
33 Tunisian @ 28,744356
34 South_Dutch @ 28,857772
35 Hungarian @ 29,073374
36 Mozabite_Berber @ 29,300621
37 Moldavian @ 29,324349
38 Austrian @ 29,355216
39 Moroccan @ 30,147365
40 Cyprian @ 30,879393
41 Sardinian @ 31,152108
42 Stuttgart @ 31,591762
43 Croatian @ 31,824275
44 East_German @ 32,163554
45 Turkish @ 33,516831
46 Lebanese_Muslim @ 34,286169
47 Syrian @ 34,926181
48 Southeast_English @ 35,147535
49 North_German @ 36,275277
50 Southwest_English @ 36,652233

Ps: (1) is not zero, cause some cut decimals in averages

Huijbregts
02-03-2016, 04:50 PM
Instead of using the GEDmatch Oracle facility to find the proximity between an individual and populations, I want to use it for population : populations. How do I do this?

I am especially interested in using the Eurogenes K13 Oracle for these populations:

Southeast English
Irish
Danish
Tuscan

I Think you can better replace Oracle with the R-program nMonte.R (https://www.dropbox.com/sh/1iaggxyc2alafow/AACIjLtnkuaNNsJ5oKME_3XHa?dl=0)

The results are:

Southeast_English
North_Atlantic Baltic West_Med West_Asian East_Med Red_Sea South_Asian East_Asian Siberian Amerindian Oceanian Northeast_African Sub.Saharan
Southeast_English 50.52000 23.27000 13.98000 4.4600 5.090000 0.09000 1.08000 0.04000 0.060000 0.620000 0.620000 0.12000 0.04000
fitted 49.86628 23.07714 14.00656 4.9674 4.377805 0.62798 1.28692 0.18604 0.331645 0.491075 0.334145 0.24284 0.19203

[1] "distance% = 1.3393 %"
[1] "percentage ancestors by pop:"

Danish West_Scottish Southwest_English Spanish_Valencia Orcadian Norwegian French_Basque
38.60 19.50 14.10 13.10 7.95 6.20 0.55



Irish
North_Atlantic Baltic West_Med West_Asian East_Med Red_Sea South_Asian East_Asian Siberian Amerindian Oceanian Northeast_African Sub.Saharan
Irish 52.23000 24.02000 12.39000 6.32000 1.410000 0.82000 1.09000 0.09000 0.03000 0.990000 0.33000 0.180000 0.10000
fitted 52.09146 23.88783 12.20068 6.00019 1.852925 0.79406 1.19681 0.12844 0.49048 0.842065 0.31111 0.077755 0.12733

[1] "distance% = 0.7937 %"
[1] "percentage ancestors by pop:"

West_Scottish Norwegian Southwest_English French_Basque Swedish Balochi Tabassaran Orcadian Karitiana
73.40 19.20 2.80 1.95 1.15 0.70 0.55 0.20 0.05



Danish
North_Atlantic Baltic West_Med West_Asian East_Med Red_Sea South_Asian East_Asian Siberian Amerindian Oceanian Northeast_African Sub.Saharan
Danish 50.04000 26.61000 10.43000 5.690000 3.610000 0.25000 1.86000 0.200000 0.27000 0.36000 0.200000 0.36000 0.100000
fitted 49.66076 26.50854 10.79576 5.738275 3.145735 0.54031 1.59855 0.267585 0.43549 0.76264 0.330925 0.11341 0.106105

[1] "distance% = 0.9646 %"
[1] "percentage ancestors by pop:"

Norwegian Southeast_English North_Dutch North_German Lebanese_Druze Piramalai Chamar Orcadian Sakilli West_Scottish Ethiopian_Gumuz
58.80 19.65 16.60 2.40 1.00 0.80 0.40 0.10 0.10 0.10 0.05



Tuscan
North_Atlantic Baltic West_Med West_Asian East_Med Red_Sea South_Asian East_Asian Siberian Amerindian Oceanian Northeast_African Sub.Saharan
Tuscan 27.18000 10.010000 23.79000 8.83000 24.59000 4.290000 0.240000 0.010000 0.29000 0.000000 0.50000 0.17000 0.09000
fitted 27.00447 9.855755 23.67875 8.77554 24.36106 4.147325 0.539095 0.330745 0.22765 0.149055 0.39929 0.43999 0.08754

[1] "distance% = 0.6665 %"
[1] "percentage ancestors by pop:"

North_Italian Italian_Jewish Lebanese_Druze Sardinian North_Dutch Italian_Abruzzo Spanish_Aragon Austrian Cyprian Southwest_French
37.25 14.95 10.30 8.05 7.30 6.95 5.85 2.60 1.70 1.25
Southeast_English Belorussian Spanish_Valencia Lebanese_Christian Serbian Yemenite_Jewish Sephardic_Jewish Central_Greek French Norwegian
1.10 0.50 0.50 0.40 0.40 0.30 0.25 0.15 0.10 0.10



West_Scottish
North_Atlantic Baltic West_Med West_Asian East_Med Red_Sea South_Asian East_Asian Siberian Amerindian Oceanian Northeast_African Sub.Saharan
West_Scottish 53.18000 23.35000 12.31000 5.560000 1.72000 0.8800 1.140000 0.050000 0.47000 0.80000 0.34000 0.080000 0.1200
fitted 52.13158 23.76758 12.81677 6.020965 1.68103 0.8086 1.048925 0.103515 0.09188 0.84842 0.37349 0.189035 0.1146

[1] "distance% = 1.3853 %"
[1] "percentage ancestors by pop:"

Irish Southwest_English Orcadian Norwegian Southeast_English
78.25 15.50 5.45 0.50 0.25
North_Dutch
0.05

Caratacus
02-03-2016, 09:10 PM
You need to get the DIY version of the calculator, the spreadsheet and a working file to use in 4mix. Then increase the number of populations listed in Oracle (20 might not cut it to get them all) then input the averages.
Do you know where I can get them from?

Mestace
02-03-2016, 10:15 PM
Do you know where I can get them from?

Actually you don't need the DIY unless you have to toy in R or use nMonte as shown above.

4mix : https://drive.google.com/file/d/0B9o3EYTdM8lQSVFBYmRWTU1GdEE/view

And the K13 file you want to use it with : 7601