G25 Results

[SUPREEEEEME]

I just got my G25 results.

These are my co-ords:

,PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC1 2,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC2 2,PC23,PC24,PC25
SUPREEEEEME_scaled,0.101303,0.135065,-0.001886,-0.036176,0.007386,-0.005857,0.002585,0.004154,0.009408,0.015855,-0.001461,-0.003897,0.001635,0.001376,0.001357,-0.006497,-0.01004,-0.003421,-0.007416,-0.009379,0.002246,-0.006306,0.001849,0.008194,0.004071

,PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC1 2,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC2 2,PC23,PC24,PC25
SUPREEEEEME,0.0089,0.0133,-0.0005,-0.0112,0.0024,-0.0021,0.0011,0.0018,0.0046,0.0087,-0.0009,-0.0026,0.0011,0.001,0.001,-0.0049,-0.0077,-0.0027,-0.0059,-0.0075,0.0018,-0.0051,0.0015,0.0068,0.0034

What are some good models to use?

This is what I was provided:

Distance: 3.1866% / 0.03186604
Aggregated
61.8 Anatolia_Tepecik_Ciftlik_N
28.4 Yamnaya_RUS_Samara
4.8 MAR_Iberomaurusian
3.2 IRN_Ganj_Dareh_N
1.2 Han
0.2 Anatolia_Barcin_N
0.2 Kura-Araxes_ARM_Kaps
0.2 WHG

I was surprised I never got any Levant PPNB

What is the difference/which is more accurate, scaled or unscaled?

Using the datasheets from the Eurogenes blog, this is what I got:

Scaled:

Modern:
25.4 Italian_Liguria
23.0 Sephardic_Jew
10.4 Tunisian_Jew
9.0 Moroccan_Jew
8.2 Samaritan
8.2 Shetlandic
4.0 Iranian_Mazandarani
3.4 Mari
2.6 Iraqi_Jew
1.4 Icelandic
1.4 Spanish_Asturias
1.2 Russian_Smolensk
0.8 Iranian_Jew
0.6 Karaite_Egypt
0.2 Sakha
0.2 Spanish_Pais_Vasco

I was expecting some Ashkenazi...

0.02660034 Ashkenazi_Jew
0.02876980 Sicilian_West
0.03260745 Italian_South
0.03265723 Maltese
0.03302688 Sicilian_East
0.03493846 Italian_Basilica
0.03513057 Italian_Abruzzo
0.03529924 Italian_Apulia
0.03537770 Italian_Campania
0.03600193 Italian_Naples
0.03640751 Italian_Molise
0.03724510 Greek_Smyrna
0.03912616 Italian_Marche
0.03983642 Italian_Calabria
0.04012249 Greek_Crete
0.04023946 Sephardic_Jew
0.04088490 Greek_Phokaia
0.04102006 Italian_Lazio
0.04176451 Italian_Jew
0.04253803 Italian_Umbria
0.04354577 Italian_Piedmont_o
0.04836352 Italian_Tuscany
0.04842779 Greek
0.04999726 Greek_Kos
0.05020086 Romaniote_Jew

Modern (without Jewish references):
27.0 Italian_Liguria
18.4 Samaritan
17.2 Karaite_Egypt
8.0 Swiss_Italian
6.2 Iranian_Mazandarani
5.6 Shetlandic
5.4 Spanish_Pais_Vasco
4.8 Spanish_Asturias
3.6 Berber_Tunisia_Chen
3.6 Mari
0.2 Sakha

0.02876980 Sicilian_West
0.03260745 Italian_South
0.03265723 Maltese
0.03302688 Sicilian_East
0.03493846 Italian_Basilica
0.03513057 Italian_Abruzzo
0.03529924 Italian_Apulia
0.03537770 Italian_Campania
0.03600193 Italian_Naples
0.03640751 Italian_Molise
0.03724510 Greek_Smyrna
0.03912616 Italian_Marche
0.03983642 Italian_Calabria
0.04012249 Greek_Crete
0.04088490 Greek_Phokaia
0.04102006 Italian_Lazio
0.04253803 Italian_Umbria
0.04354577 Italian_Piedmont_o
0.04836352 Italian_Tuscany
0.04842779 Greek
0.04999726 Greek_Kos
0.05284233 Swiss_Italian
0.05312040 Albanian
0.05314759 Italian_Piedmont
0.05525948 Italian_Liguria

Ancient:
17.0 Anatolia_Kaman-Kalehoyuk_MLBA_low_res
16.8 Levant_ISR_Ashkelon_LBA
12.6 DEU_MA_o
12.0 KAZ_Ak_Moustafa_MLBA1
11.4 HRV_IA
11.0 ITA_Boville_Ernica_IA
4.4 MAR_Iberomaurusian
4.2 TKM_Gonur3_BA
2.0 BGR_Varna_En3
2.0 RUS_Petrovka_MLBA
1.6 UKR_N_o
1.4 Baltic_LTU_Late_Antiquity_low_res
1.2 Anatolia_Kumtepe_N_low_res
1.0 RUS_Devils_Gate_Cave_N
1.0 RUS_Saltovo-Mayaki_low_res
0.2 MAR_EN
0.2 PAK_Saidu_Sharif_H_o

0.03780525 Levant_LBN_MA_Mixed
0.03805693 IND_Roopkund_B
0.04041378 ITA_Rome_Late_Antiquity
0.04106929 ITA_Tivoli_Renaissance
0.04206598 ITA_Rome_MA
0.04750721 ITA_Rome_Imperial
0.04956895 ITA_Collegno_MA_o1
0.05043602 ITA_Ardea_Latini_IA_o
0.05427259 Ostrogothic_Crimea_ACD
0.05641262 ITA_Prenestini_tribe_IA_o
0.05641341 Scythian_MDA
0.05778000 Iberia_Southeast_c.10-16CE
0.05904471 ITA_Proto-Villanovan
0.06082158 HUN_BA_o
0.06346565 Iberia_Southeast_c.5-8CE
0.06374765 HRV_EBA
0.06397310 Iberia_Southeast_c.3-4CE
0.06638987 DEU_MA_o
0.06728873 BGR_IA
0.06885357 ARM_Areni_C
0.06891825 Iberia_Northeast_c.8-12CE
0.06916247 HRV_IA
0.07187378 IND_Roopkund_B_o
0.07229688 Iberia_Northeast_Empuries2
0.07235166 Anatolia_Barcin_C

Unscaled:

Modern:
36.2 Sephardic_Jew
15.8 Spanish_Asturias
12.2 Iraqi_Jew
10.4 Shetlandic
8.4 Karaite_Egypt
5.0 Berber_Tunisia_Chen
3.4 Mari
2.2 Russian_Smolensk
1.8 Sakha
1.0 Biaka
1.0 Gupta
1.0 Han_NChina
0.8 Sherpa
0.2 Mozabite
0.2 Saharawi
0.2 Samaritan
0.2 She

0.01544677 Ashkenazi_Jew
0.01637632 Sephardic_Jew
0.01805498 Sicilian_West
0.01866282 Maltese
0.01932223 Italian_Jew
0.02001873 Sicilian_East
0.02042563 Italian_Marche
0.02099873 Italian_Naples
0.02111377 Italian_Abruzzo
0.02116783 Italian_Apulia
0.02121778 Italian_Campania
0.02131953 Italian_South
0.02167020 Syrian_Jew
0.02178312 Tunisian_Jew
0.02218409 Romaniote_Jew
0.02228121 Moroccan_Jew
0.02230219 Italian_Basilica
0.02243680 Italian_Molise
0.02288877 Libyan_Jew
0.02302169 Italian_Lazio
0.02337806 Greek_Smyrna
0.02360509 Greek_Crete
0.02381696 Italian_Piedmont
0.02429721 Italian_Umbria
0.02439631 Swiss_Italian

Modern(without Jewish references):
21.2 Karaite_Egypt
18.4 Spanish_Asturias
12.6 Italian_Liguria
12.0 Samaritan
8.0 Berber_Tunisia_Chen
8.0 Shetlandic
7.2 Iranian_Mazandarani
4.4 Mari
3.8 Italian_Naples
1.8 Sakha
0.8 Japanese
0.8 She
0.6 Biaka
0.4 Gupta

0.01805498 Sicilian_West
0.01866282 Maltese
0.02001873 Sicilian_East
0.02042563 Italian_Marche
0.02099873 Italian_Naples
0.02111377 Italian_Abruzzo
0.02116783 Italian_Apulia
0.02121778 Italian_Campania
0.02131953 Italian_South
0.02230219 Italian_Basilica
0.02243680 Italian_Molise
0.02302169 Italian_Lazio
0.02337806 Greek_Smyrna
0.02360509 Greek_Crete
0.02381696 Italian_Piedmont
0.02429721 Italian_Umbria
0.02439631 Swiss_Italian
0.02474874 Italian_Liguria
0.02484464 Italian_Tuscany
0.02487861 Italian_Calabria
0.02553891 Italian_Lombardy
0.02572781 Italian_Piedmont_o
0.02633362 Turkish_Balikesir
0.02665342 Karaite_Egypt
0.02666440 Greek_Phokaia

Ancient:
14.6 Levant_ISR_Ashkelon_LBA
11.6 Anatolia_Kaman-Kalehoyuk_MLBA_low_res
11.2 KAZ_Ak_Moustafa_MLBA1
10.0 ITA_Boville_Ernica_IA
8.4 TKM_Gonur3_BA
7.2 HUN_MA_Szolad_o1
6.6 DEU_MA_o
6.6 UKR_N_o
5.2 Anatolia_Kumtepe_N_low_res
5.0 MAR_Iberomaurusian
3.6 England_EMBA
3.6 Wales_CA_EBA
1.8 Baltic_LTU_Late_Antiquity_low_res
1.8 JPN_Jomon
1.2 RUS_Yana_MA
1.0 KEN_Pastoral_N_o
0.4 NPL_Samdzong_1500BP
0.2 MAR_EN

0.02089581 Levant_LBN_MA_Mixed
0.02170578 ITA_Rome_MA
0.02347381 ITA_Rome_Late_Antiquity
0.02391237 ITA_Rome_Imperial
0.02512618 IND_Roopkund_B
0.02689163 ITA_Proto-Villanovan
0.02702832 HUN_BA_o
0.02716283 ITA_Collegno_MA_o1
0.02756316 Iberia_Southeast_c.10-16CE
0.02792078 ITA_Ardea_Latini_IA_o
0.02792774 ITA_Tivoli_Renaissance
0.02958429 Iberia_Northeast_c.8-12CE
0.02996941 Scythian_MDA
0.03031039 HRV_IA
0.03045341 ITA_Collegno_MA_o2
0.03108882 Iberia_Southeast_c.5-8CE
0.03112030 DEU_MA_ACD
0.03150952 Ostrogothic_Crimea_ACD
0.03155339 Levant_LBN_MA_NE
0.03211173 ARM_Areni_C
0.03224485 Iberia_Southeast_c.3-4CE
0.03250219 ITA_Rome_Renaissance
0.03283611 IND_Roopkund_B_o
0.03288161 Anatolia_IA
0.03333722 ITA_Prenestini_tribe_IA_o

[vbnetkhio]

What is the difference/which is more accurate, scaled or unscaled?


this is what the man who created nMonte says:
https://anthrogenica.com/showthread.php?16264-Scaled-or-unscaled-penalty-on-or-off&p=536704&viewfull=1#post536704

in short, unscaled is more accurate

[Kamal900]

Your ancient genetic components:

"sample": "Test1:SUPREEEEEME_scaled",
"fit": 2.4687,
"Levant_LBN_Roman": 27.5,
"Iberia_Northeast_Empuries2": 26.67,
"DEU_MA": 25,
"IRN_Hajji_Firuz_BA": 11.67,
"Canary_Islands_Guanche": 9.17,

Modern averaged results:

"sample": "Test1:SUPREEEEEME_scaled",
"fit": 2.3688,
"Lebanese_Christian": 35.83,
"Spanish_Aragon": 32.5,
"Iranian_Fars": 13.33,
"CZE_Early_Slav": 12.5,
"Berber_Tunisia_Chen": 5.83,

ancient averaged results distance:

Distance to: SUPREEEEEME_scaled
0.03780525 Levant_LBN_MA_Mixed
0.03805693 IND_Roopkund_B
0.04041378 ITA_Rome_Late_Antiquity
0.04106929 ITA_Tivoli_Renaissance
0.04206598 ITA_Rome_MA
0.04750721 ITA_Rome_Imperial
0.04956895 ITA_Collegno_MA_o1
0.05043602 ITA_Ardea_Latini_IA_o
0.05427259 Ostrogothic_Crimea_ACD
0.05641262 ITA_Prenestini_tribe_IA_o
0.05641341 Scythian_MDA
0.05778000 Iberia_Southeast_c.10-16CE
0.05904471 ITA_Proto-Villanovan
0.06082158 HUN_BA_o
0.06346565 Iberia_Southeast_c.5-8CE
0.06374765 HRV_EBA
0.06397310 Iberia_Southeast_c.3-4CE
0.06638987 DEU_MA_o
0.06728873 BGR_IA
0.06885357 ARM_Areni_C
0.06891825 Iberia_Northeast_c.8-12CE
0.06916247 HRV_IA
0.07187378 IND_Roopkund_B_o
0.07229688 Iberia_Northeast_Empuries2
0.07235166 Anatolia_Barcin_C

ancient samples distance:

Distance to: SUPREEEEEME_scaled
0.02791771 ITA_Rome_MA:RMPR60
0.03498784 ITA_Rome_MA:RMPR1290
0.03633610 ITA_Rome_MA:RMPR64
0.03674449 ITA_Rome_MA:RMPR53
0.03699391 IND_Roopkund_B:I3348
0.03749569 ITA_Rome_Imperial:RMPR1549
0.03914019 ITA_Rome_Late_Antiquity:RMPR122
0.03924292 ITA_Rome_MA:RMPR58
0.03930285 ITA_Rome_Imperial:RMPR1544
0.04018394 ITA_Rome_Late_Antiquity:RMPR136
0.04025614 ITA_Rome_Imperial:RMPR835
0.04046873 ITA_Rome_MA:RMPR59
0.04057114 IND_Roopkund_B:I6937
0.04129026 ITA_Rome_Imperial:RMPR50
0.04134346 Levant_LBN_MA_Mixed:SI-53
0.04171541 ITA_Rome_Late_Antiquity:RMPR120
0.04204245 ITA_Rome_MA:RMPR57
0.04220684 ITA_Rome_MA:RMPR56
0.04231901 ITA_Rome_Imperial:RMPR131
0.04250513 ITA_Rome_MA:RMPR54
0.04345843 ITA_Rome_Imperial:RMPR114
0.04352057 ITA_Rome_Imperial:RMPR47
0.04355054 ITA_Collegno_MA:CL121
0.04358281 ITA_Tivoli_Renaissance:RMPR973
0.04410510 ITA_Tivoli_Renaissance:RMPR970

[Leto]

Modern averaged results:

"sample": "Test1:SUPREEEEEME_scaled",
"fit": 2.3688,
"Lebanese_Christian": 35.83,
"Spanish_Aragon": 32.5,
"Iranian_Fars": 13.33,
"CZE_Early_Slav": 12.5,
"Berber_Tunisia_Chen": 5.83,

Why Spain and Iran? Why not Italy and Poland or Belarus?

[SUPREEEEEME]

I had heard that using these 4 populations for Ashkenazi Jews is pretty good:
Italian Bergamo
Levant_Canaanite_MBA
DEU_MA
HUN_Tisza_LN

I got:
45.6 Levant_Canaanite_MBA
28.8 DEU_MA
25.6 Italian_Bergamo

[vbnetkhio]

I had heard that using these 4 populations for Ashkenazi Jews is pretty good:
Italian Bergamo
Levant_Canaanite_MBA
DEU_MA
HUN_Tisza_LN

I got:
45.6 Levant_Canaanite_MBA
28.8 DEU_MA
25.6 Italian_Bergamo

distance? 2-3 is a good distance

[Calpurnius]

As for accuracy of scaled vs unscaled, it depends on what you want to do. I think scaled are nevertheless useful, for one every time you want to compute something where accuracy of distance matters, like obviously single item distances but also PCA, which to be realistic should have this rescaling.
For modelling itself, it's a double edged sword. Regardless of how the algorithm does it, either stocastically like like nMonte or doing something like projected gradient descent, you are always minimizing an euclidean distance. If your model consists of (truly)distant sources but their distance isn't well represented because the variance of each dimension is the same, then you may get unexpected results like e.g sub saharan African ancestry popping up in Karelians or deeply east Asian ancestry showing up in Italy. The downside of scaling though as the link posted above is that it has the opposite effect on those dimensions that are useful to distinguish more closely related sources, which basically get overwhelmed by the "weight" so to speak of the scaled lower dimensions.
So perhaps if you are dealing with a distal model, then use scaled ones, perhaps with some penalty. Otherwise if you are dealing with a model with more closely related sources, unscaled with no penalty may be better.

[Peterski]

distance? 2-3 is a good distance

I think below 2 is very good.

I've been playing with my own coordinates during the last few days on a Polish forum, and I got some models with fits less than 2.

I used only ancient samples.

Anything with distance above 2 is probably not a very probbable, accurate representation of your ancestry, but just approximation.

This is why e.g. Irish users like Grace don't get distances below 2 when there is no Insular Celt pop. in the model but just Germanic.

=====

Here is one of models with fit below 2 for me:

(I used scaled coordinates for this model)

https://i.imgur.com/nWEEcr9.png

If I remove Poprad (Migration Period Slovakia), I get high Celtic. If I remove Proto-Villanova, it is split between few populations.

Romans include Latini, Republic and Imperial - but my 1.6% is from Imperial. Scythians include Moldova, Hungary and RU_Urals.

IIRC only after the inclusion of Poprad the fit dropped below 2. Without Poprad it was slightly over 2 and I was scoring high Celtic.

Germanic_North&West includes:

DEU_MA
SWE_IA
DNK_BA

The assumption that Poprad chieftain was a Vandal is of course speculative, but it is probable (Vandals migrated through Poprad).

=====

Edit:

This one is similar but without Proto-Villanova, the fit is slightly worse but still below 2:

https://i.imgur.com/OEWQF9o.png

I included Proto-Villanova because I've heard it could be related to the Venetic tribes.

=====

Between 1 and 2 is the kind fit you should be aiming for, and it narrows down your options.

If you are fine with fits like 2-3 then you can model yourself in a bazzillion of different ways.

I can be modelled in 100 different ways with 100 different populations and get fits 2-3.

But models that have fits like 1-2 are hard to find and just several options are possible.

=======
By the way:

Szolad is not a homogenous population, just check this:

https://www.theapricity.com/forum/showthread.php?289030-Collegno-Longobards-on-GEDmatch-Genesis&p=6336063&viewfull=1#post6336063

https://i.imgur.com/pKzwdIJ.png

https://i.imgur.com/K3isp18.png
I just selected these samples to use as ethnic Longobards:
(four of them are unrelated, one is from Kindred SZ1 family)


Longobards:HUN_MA_Szolad:SZ4,0.134311,0.133034,0.0 64488,0.056525,0.035699,0.021196,0.011751,0.007154 ,-0.001841,0.004191,-0.005846,0.001649,-0.013082,-0.001376,0.026465,-0.002519,-0.024121,0.004687,0.00176,-0.004002,0.006988,0.007543,0.004067,0.013737,0.001 796
Longobards:HUN_MA_Szolad:SZ2,0.122929,0.139128,0.0 70144,0.067184,0.038469,0.018128,0.00611,0.006461,-0.000205,-0.009294,-0.000974,-0.00015,-0.008474,-0.00055,0.017372,-0.006629,-0.022296,0.005954,0.005908,-0.004627,0.015597,0.000742,0.007395,0.008555,0.002 634
Longobards:HUN_MA_Szolad:SZ9,0.138864,0.125926,0.0 69013,0.066861,0.036622,0.03012,0.00188,0.011999,0 .011658,-0.000547,-0.011692,0.003597,-0.008176,-0.003716,0.029994,-0.001193,-0.00665,0.001394,0.00088,0.007629,0.011355,0.00581 2,-0.003451,0.014942,-0.001796
Longobards:HUN_MA_Szolad:SZ16,0.133173,0.128972,0. 068259,0.062662,0.035699,0.019522,0.002585,0.00992 3,0.001432,-0.005832,0.001137,0.008992,-0.005946,-0.006881,0.024158,0.006232,-0.008084,-0.000253,-0.003017,0.009004,0.003244,0.005193,0.001109,0.014 219,0.003353
Longobards:HUN_MA_Szolad:SZ7,0.135449,0.135065,0.0 66373,0.062016,0.035083,0.01255,0.00611,0.005307,0 .003272,0,-0.011205,3e-04,-0.007433,-0.010322,0.018729,0.002784,-0.005476,0.000127,0.001885,0.002376,0.009234,0.007 419,0.001602,0.015785,-0.001197

[SUPREEEEEME]

distance? 2-3 is a good distance

2.8293

[Leto]

@SUPREEEEEME
Please run this model - Samaritan, Swiss-Italian, Polish

[SUPREEEEEME]

@SUPREEEEEME
Please run this model - Samaritan, Swiss-Italian, Polish

Distance: 2.7050% / 0.02705007
Aggregated
52.8 Swiss_Italian
37.6 Samaritan
9.6 Polish

[Leto]

Distance: 2.7050% / 0.02705007
Aggregated
52.8 Swiss_Italian
37.6 Samaritan
9.6 Polish
The Samaritan is way lower than 50%. Strange.

[SUPREEEEEME]

The Samaritan is way lower than 50%. Strange.

I should add that that's with scaled. I'll try unscaled tomorrow.

[Pine]

I just got my G25 results.



Egyptian Karaite is a Jewish reference, and not just religiously. It may have some Aegean admixture too.

[Pine]

@SUPREEEEEME
Please run this model - Samaritan, Swiss-Italian, Polish

Why Swiss-Italian?

[marco]

Is unscaled really more accurate?

[Bakha]

Your default analysis by David looks similar to mine:

Target: Uzbek/Tatar/Russian_scaled
Distance: 4.2280% / 0.04228024
Aggregated
42.2 Yamnaya_RUS_Samara
35.0 Anatolia_Tepecik_Ciftlik_N
7.0 Han
5.0 WHG
4.0 Nganassan
3.4 IRN_Shahr_I_Sokhta_BA3
1.4 IRN_Ganj_Dareh_N
1.0 Dinka
1.0 Kura-Araxes_ARM_Kaps

Are you sure you r Jewish and not Uzbek/Tatar?

[Pine]

The Samaritan is way lower than 50%. Strange.

Use Lebanese Christian instead of Samaritan. Samaritans became endogamous before the rest of the Levant. They may be missing admixture received by Judeans later and based on what I've seen - likely do.

Even I score below 50% Samaritan, which is rare for me:

Using Vahaduo (defaults to a penalty of 0 , with other peculiarities, but using it since I think Supreme did as well):

Target: Me_scaled
Distance: 2.3785% / 0.02378495
Aggregated
53.0 Swiss_Italian
47.0 Samaritan

Whereas, with Lebanese Christian (who were determined to be pretty much pure Canaanites in a study):

Target: Me_scaled
Distance: 2.1626% / 0.02162611
Aggregated
55.2 Lebanese_Christian
44.8 Swiss_Italian

And notice that the fit distance is lower with Lebanese Christian. No, I didn't forget to add Polish in there; it just was evaluated to 0.

[SUPREEEEEME]

Your default analysis by David looks similar to mine:

Target: Uzbek/Tatar/Russian_scaled
Distance: 4.2280% / 0.04228024
Aggregated
42.2 Yamnaya_RUS_Samara
35.0 Anatolia_Tepecik_Ciftlik_N
7.0 Han
5.0 WHG
4.0 Nganassan
3.4 IRN_Shahr_I_Sokhta_BA3
1.4 IRN_Ganj_Dareh_N
1.0 Dinka
1.0 Kura-Araxes_ARM_Kaps

Are you sure you r Jewish and not Uzbek/Tatar?

Are you sure you are Uzbek/Tatar and not Jewish? XD

Anyways, saying our results are similar is a stretch - they're quite different.

[Pine]

Are you sure you are Uzbek/Tatar and not Jewish? XD

Anyways, saying our results are similar is a stretch - they're quite different.

Bakha hasn't yet figured out that Davidski checks everyone against a few, carefully picked references.

[fcuic]

Sorry for the maybe obvious question, but how can i run nmonte global 25?? Google-ing didnt help cause site is broken. Thanks, i am new to this forum.

[Pine]

Sorry for the maybe obvious question, but how can i run nmonte global 25?? Google-ing didnt help cause site is broken. Thanks, i am new to this forum.

Do you have your coordinates?

[Bakha]

Are you sure you are Uzbek/Tatar and not Jewish? XD

Anyways, saying our results are similar is a stretch - they're quite different.
Was jk obviously not

[fcuic]

How to get the coordinates, i just cant find the answer. Global25 is the most precise model of all i think.