happycow's G25 results

[Kamal900]

Here's prince of persia's results:

nMonite:

https://i.ibb.co/z5XSsGC/2.png
https://i.ibb.co/MhXtFWg/1.png

Dayum son, you're more Berber and Arabian than me, rofl.

Here's Algerian, Iranian Fars, Greek, and Canaanite ancestries, and it's not a good fit(the lesser the number, the better):

https://i.ibb.co/ZxHs1Dc/3.png

So, I removed Algerian with Egyptian, and sure enough, Egyptian was a far better fit:

https://i.ibb.co/7CkMt70/5.png

So..you don't seem to have much European admixture and Caucasian affiliation like me, and it seems that you have higher Egyptian and Arabian admixtures. I think it's very typical for someone from the WB of Palestine.

Here are his coordinates:

,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
TimA_scaled,0.053497,0.135065,-0.048649,-0.07429,-0.009848,-0.027331,-0.009635,-0.004384,0.009613,0.002916,0.006333,-0.003747,0.017096,-0.000275,-0.003936,0.005967,-0.001565,0,0.003017,0.01063,0.003993,-0.006183,0.000246,-0.001205,0.000958

,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
TimA,0.0047,0.0133,-0.0129,-0.023,-0.0032,-0.0098,-0.0041,-0.0019,0.0047,0.0016,0.0039,-0.0025,0.0115,-0.0002,-0.0029,0.0045,-0.0012,0,0.0024,0.0085,0.0032,-0.005,0.0002,-0.001,0.0008

This should be interesting.

[happycow]

Very cool. That Egyptian though.... rofl.

What is Iranian Fars?

[Kamal900]

Very cool. That Egyptian though.... rofl.

What is Iranian Fars?

I know, right? You should start listening to 7akeem. I guess it's Persian from the province of Far or Pars in Iran.

[happycow]

I know, right? You should start listening to 7akeem. I guess it's Persian from the province of Far or Pars in Iran.

I guess that's where I get my look from. :p Lol.

I assumed I would have more berber and arabian than you just based off my gedmatch results. I expected similar European though since my gedmatch results were more Euro shifted.

[Kamal900]

I guess that's where I get my look from. :p Lol.

I assumed I would have more berber and arabian than you just based off my gedmatch results. I expected similar European though since my gedmatch results were more Euro shifted.

In my opinion, you look more Persian than masri, but at the same time, there are Egyptians who have your look, rofl.

[happycow]

In my opinion, you look more Persian than masri, but at the same time, there are Egyptians who have your look, rofl.

I've only met one Egyptian my whole life. Most of the MENA folk here are either Levantines or Persians.

[Kamal900]

I've only met one Egyptian my whole life. Most of the MENA folk here are either Levantines or Persians.

Makes sense, honestly. The largest Arab group here after the locals are Egyptians, and they're a decent folk.

[Token]

Don't mix up ancient with modern samples, that confuses the hell out of the PCA.

[Kelmendasi]

I'll do some runs for him as well

Ph2ter 2000BCE-2500BCE calc:
Fit - 2.2075
Levant - 65
Anatolia_EBA - 11.67
Bactria-Margiana - 10
Iberomaurusian - 5.83
Beakers_Central Europe - 3.33
Beakers_Hungary - 1.67
Beakers_Britain - 0.83
Indus valley - 0.83
No steppe central European - 0.83

Iron Age world K19:
Fit - 1.714
SW Asian - 65.83
Caucasian - 20
North African - 4.17
Med - 3.33
Indo-Aryan - 2.5
Europe - 1.67
SSA - 0.83
Central Asian - 0.83
East African - 0.83

[Lemgrant]

nMonte3, pen=0.001

individual references

getMonte('Global_25_PCA_scaled.txt', 'target.txt')

[1] "1. CLOSEST SINGLE ITEM DISTANCE%"
Palestinian:S_Palestinian-3 Palestinian:HGDP00676
2.303747 2.528072
Palestinian:S_Palestinian-2 Palestinian:HGDP00690
2.588282 2.714034
Palestinian:HGDP00689 Palestinian:HGDP00677
2.753288 2.809034
Palestinian:HGDP00675 BedouinA:HGDP00626
2.994320 3.067842

[1] "distance%=1.1688"

TimA_scaled

Palestinian,31.4
BedouinA,10.2
Lebanese_Muslim,9.8
Lebanese_Druze,4.8
Druze,2.8
Lebanese_Christian,2.6
BedouinB,2.2
Egyptian,1.8
Levant_ChL,1.8
Tunisian_Jew,1.8
Iraqi_Jew,1.4
Mozabite,1.4
Yemenite_Amran,1.4
Yemenite_Dhamar,1.2
Yemenite_Jew,1.2
Seh_Gabi_ChL,1
Abkhasian,0.8
Azeri_Iran,0.8
Greek_Trabzon,0.8
Levant_BA_North,0.8
Samaritan,0.8
Tunisian,0.8
Anatolia_MLBA,0.6
Armenian,0.6
Cypriot,0.6
England_Roman_o,0.6
Greek_Central_Anatolia,0.6
Hajji_Firuz_ChL,0.6
Iranian_Zoroastrian,0.6
Karachay,0.6
Romaniote_Jew,0.6
Saudi,0.6
Sephardic_Jew,0.6
Yemenite_Mahra,0.6
Assyrian,0.4
Iranian_Fars,0.4
Italian_Abruzzo,0.4
Levant_N,0.4
Libyan,0.4
Moroccan,0.4
Turkish_Istanbul,0.4
Yemenite_Ma'rib,0.4
Adygei,0.2
Anatolia_BA,0.2
Anatolia_EBA,0.2
Armenia_EBA,0.2
Ashkenazi_Jew,0.2
Baden_LCA,0.2
Balkans_BA,0.2
Balkans_N,0.2
Balochi,0.2
Bantu_Kenya,0.2
Beaker_Central_Europe,0.2
Cherkes,0.2
Dinka,0.2
Dzharkutan1_BA,0.2
Ganj_Dareh_N,0.2
Georgian_Imer,0.2
Georgian_Jew,0.2
Georgian_Laz,0.2
Iranian_Jew,0.2
Iranian_Lor,0.2
Iranian_Persian,0.2
Italy_Medieval_Collegno_o1,0.2
Jordanian,0.2
Kabardin,0.2
Levant_BA_South,0.2
Libyan_Jew,0.2
Maltese,0.2
Mandenka,0.2
Minoan_Lasithi,0.2
Moroccan_Jew,0.2
Mycenaean,0.2
Natufian,0.2
Sappali_Tepe_BA,0.2
Scottish,0.2
Sudanese,0.2
Tabasaran,0.2
Tajik_Rushan,0.2
Tepe_Hissar_ChL,0.2
Tepecik_Ciftlik_N,0.2
Yemenite_Al_Bayda,0.2

datasheet with averages, pen=0.001

getMonte('Global_25_PCA_pop_averages_scaled.txt', 'target.txt')
[1] "1. CLOSEST SINGLE ITEM DISTANCE%"
Palestinian Lebanese_Muslim BedouinA Lebanese_Druze
2.042460 3.217404 3.538382 3.956824
Lebanese_Christian Druze Libyan_Jew Tunisian_Jew
4.232289 4.286739 4.307304 4.510809


[1] "distance%=1.3148"

TimA_scaled

Palestinian,23
BedouinA,4.8
Lebanese_Muslim,4.8
England_Roman_o,3.2
Lebanese_Christian,2.4
Lebanese_Druze,2.2
Levant_BA_North,2.2
Iraqi_Jew,2
Jordanian,2
Levant_BA_South,2
Tunisian_Jew,2
BedouinB,1.8
Druze,1.8
Libyan,1.8
Saudi,1.8
Yemenite_Jew,1.8
Armenian,1.6
Libyan_Jew,1.6
Greek_Trabzon,1.4
Yemenite_Dhamar,1.4
Cypriot,1.2
Hajji_Firuz_ChL,1.2
Hasanlu_IA,1
Algerian,0.8
Anatolia_BA,0.8
Anatolia_MLBA,0.8
Egyptian,0.8
Hajji_Firuz_ChL_o,0.8
Levant_ChL,0.8
Sephardic_Jew,0.8
Syrian_Jew,0.8
Turkish_Trabzon,0.8
Yemenite_Amran,0.8
Yemenite_Ma'rib,0.8
Yemenite_Mahra,0.8
Anatolia_EBA,0.6
Greek_Central_Anatolia,0.6
Iranian_Fars,0.6
Iranian_Lor,0.6
Krepost_N,0.6
Mozabite,0.6
Tunisian,0.6
Yemenite_Al_Bayda,0.6
Armenia_MLBA,0.4
Barcin_N,0.4
CHG,0.4
Dzharkutan1_BA,0.4
Iranian_Persian,0.4
Iranian_Zoroastrian,0.4
Italian_Jew,0.4
Moroccan,0.4
Natufian,0.4
Parkhai_Eneolithic,0.4
Romaniote_Jew,0.4
Samaritan,0.4
Seh_Gabi_ChL,0.4
Sumbar_LBA,0.4
Tepecik_Ciftlik_N,0.4
Turkish_Aydin,0.4
Turkish_Kayseri,0.4
Abkhasian,0.2
Alan,0.2
Anatolia_ChL,0.2
Anatolia_MLBA_low_res,0.2
Ashkenazi_Jew,0.2
Assyrian,0.2
Avar,0.2
Azeri,0.2


results with pen=0:

getMonte('Global_25_PCA_scaled.txt', 'target.txt', pen=0)

[1] "distance%=0.2854"

TimA_scaled

Yemenite_Jew,15
Levant_ChL,10.4
Egyptian,8.8
Armenian,7.8
Iraqi_Jew,5.2
Mycenaean,5.2
Hajji_Firuz_ChL_o,4.2
Turkish_Trabzon,2.8
German,2.4
Gonur1_BA,2.2
Lebanese_Christian,2.2
Moroccan,2.2
Seh_Gabi_ChL,2.2
Saudi,2
BedouinB,1.6
Anatolia_EBA,1.4
CHG,1.4
Georgian_Jew,1.4
Tunisian,1.4
Dutch,1.2
Hajji_Firuz_ChL,1.2
Parkhai_Eneolithic,1.2
Saharawi,1.2
Ukraine_N_o,1.2
Anatolia_BA,1
Jordanian,1
Georgian_Laz,0.8
Iberomaurusian,0.8
Iranian_Jew,0.8
Yemenite_Mahra,0.8
Yoruba,0.8
Belgian,0.6
Luhya_Kenya,0.6
Scythian_Moldova,0.6
Tepecik_Ciftlik_N,0.6
Abkhasian,0.4
Algerian,0.4
England_Roman_o,0.4
Levant_N,0.4
Parkhai_LBA,0.4
Tepe_Hissar_ChL,0.4
Adygei,0.2
Armenia_EBA,0.2
Bantu_Kenya,0.2
Eritrean,0.2
Esan_Nigeria,0.2
French,0.2
Greece_N,0.2
Greek_Trabzon,0.2
Greenlander_East,0.2
Karitiana,0.2
Minoan_Lasithi,0.2
Mozabite,0.2
Seh_Gabi_LN,0.2
Sephardic_Jew,0.2
Tepe_Anau_Eneolithic,0.2
Tisza_LN,0.2
Yemenite_Ma'rib,0.2


getMonte('Global_25_PCA_pop_averages_scaled.txt', 'target.txt', pen=0)

[1] "distance%=0.6826"

TimA_scaled

Yemenite_Jew,20.2
Hajji_Firuz_ChL_o,16.6
England_Roman_o,11
Mycenaean,10
Anatolia_BA,9
Parkhai_LBA,4.4
Levant_N,4
CHG,3.6
Natufian,3
Tepecik_Ciftlik_N,3
Jordanian,2.8
Iberomaurusian,2
Bantu_Kenya,1.4
Seh_Gabi_LN,1.2
Moroccan,1
Eritrean,0.8
Remedello_BA,0.8
Anatolia_IA_low_res,0.6
Greenlander_East,0.6
Hasanlu_IA,0.6
Golden_Horde_European,0.4
Greece_N,0.4
Iberia_Central_CA,0.4
Luhya_Kenya,0.4
Saudi,0.4
Ukraine_N_o,0.4
Yoruba,0.4
Krepost_N,0.2
Papuan,0.2
Sweden_MN,0.2

[happycow]

Don't mix up ancient with modern samples, that confuses the hell out of the PCA.

I see. what samples would you use in this case? interested in seeing the results.

[Kamal900]

bump

[Mingle]

So he's only 40% Paleo-Levantine? Wow, that's low.

[Kamal900]

So he's only 40% Paleo-Levantine? Wow, that's low.

I'm somewhat low as well.
https://www.theapricity.com/forum/showthread.php?271698-My-G25-coordiniates-have-arrived!

I guess it's simply because me and him have high Arabian and Berber mixtures. The only difference is that I'm more Caucasian shifted and European admixed than him.

[happycow]

So he's only 40% Paleo-Levantine? Wow, that's low.

I know... :( lol

[Kamal900]

I know... :( lol

At least it's better than nothing, lol. Me and you are partially Canaanites, so that makes us natives to the land.

[Sikeliot]

At least it's better than nothing, lol. Me and you are partially Canaanites, so that makes us natives to the land.

I have less Canaanite ancestry than you but I am proud of mine as well.

[happycow]

At least it's better than nothing, lol. Me and you are partially Canaanites, so that makes us natives to the land.

Indeed. It's all very interesting no doubt.

[Kamal900]

bump

[StonyArabia]

Very interesting it seems he is also is Arab and Berber shifted

[Kamal900]

Very interesting it seems he is also is Arab and Berber shifted

Do you know why?

[happycow]

Very interesting it seems he is also is Arab and Berber shifted

My gedmatch results seemed to shift me towards NA

[Kamal900]

My gedmatch results seemed to shift me towards NA

Most likely it's Berber ancestry. Maybe you need to check on your genealogy. Ask your parents about it.

[happycow]

Most likely it's Berber ancestry. Maybe you need to check on your genealogy. Ask your parents about it.

Yeah I'll have to pick their brains again. I've definitely been left with more questions than answers thats for sure lol.

[Kelmendasi]

His results from the K14 ancient world calc:
Fit - 3.968
Levant 7300-6700BC - 60
Caucasus 7900-7500BC - 29.17
South Asia modern proxy - 3.33
Eastern Europe 9386-9231BC - 2.50
Northwest Africa 13000-12000BC - 1.67
Anatolia 8300-7900BC - 1.67
West Africa modern proxy - 0.83
Western Europe 11100-10800BC - 0.83

[Astarte]

Where can I find this calc?

[Kelmendasi]

Where can I find this calc?
You need to pay Davidski for G25 http://bga101.blogspot.com/2018/02/the-powerful-global-25-now-available.html

[happycow]

Forgot to post the results from the man himself. Why is my Levant_N so low? :confused:

[1] "distance%=4.3587"

TimA_scaled

Barcin_N,35.4
Armenia_EBA,32.8
Ganj_Dareh_N,13
Iberomaurusian,10
Levant_N,7
Ethiopia_4500BP,1.8

[Kamal900]

Forgot to post the results from the man himself. Why is my Levant_N so low? :confused:

[1] "distance%=4.3587"

TimA_scaled

Barcin_N,35.4
Armenia_EBA,32.8
Ganj_Dareh_N,13
Iberomaurusian,10
Levant_N,7
Ethiopia_4500BP,1.8

The distance is really bad. Anything that is in the range between 0 and 1.5 are considered to be accurate. Anything that is greater than 1.5 or 2 is very inaccurate.

[happycow]

The distance is really bad. Anything that is in the range between 0 and 1.5 are considered to be accurate. Anything that is greater than 1.5 or 2 is very inaccurate.

Gotcha. Thanks!

[Mingle]

The distance is really bad. Anything that is in the range between 0 and 1.5 are considered to be accurate. Anything that is greater than 1.5 or 2 is very inaccurate.Not really. Its normal for calcs comprising of ancient components to get such large fits.

Also, fits below 1-1.5 are overfitting and considered bad as well.

[happycow]

Not really. Its normal for calcs comprising of ancient components to get such large fits.

Also, fits below 1-1.5 are overfitting and considered bad as well.

I see. So what do you think of the results provided? Nothing out of the ordinary? :confused:

[Mingle]

I see. So what do you think of the results provided? Nothing out of the ordinary? :confused:Probably. I'll look at them properly when I get home.

[happycow]

Probably. I'll look at them properly when I get home.

ok thx

[Mingle]

You get much more Natufian (Levant NF) on my calc which is only for the Neolithic Age. I don't know why you scored so little with Davidski's calc. Less than 10% Natufian does seem unusually low for people from your region.


Target: TimA
Distance: 2.2728% / 0.02272842
Aggregated
32.2 Anatolia_NF
31.6 Levant_NF
18.0 Iran_NF
14.2 Caucasus_HG
2.4 SSA
1.2 West_Siberia_HG
0.4 Eastern_HG

You score very similarly to the Palestinian average, so your results are quite typical.


Target: Palestinian
Distance: 2.6575% / 0.02657505
Aggregated
34.6 Levant_NF
30.2 Anatolia_NF
20.6 Iran_NF
10.0 Caucasus_HG
2.8 SSA
1.4 West_Siberia_HG
0.4 Eastern_HG

[happycow]

You get much more Natufian (Levant NF) on my calc which is only for the Neolithic Age. I don't know why you scored so little with Davidski's calc. Less than 10% Natufian does seem unusually low for people from your region.



You score very similarly to the Palestinian average, so your results are quite typical.

Awesome thank you very much!!! :cool::cool:

[Kamal900]

You get much more Natufian (Levant NF) on my calc which is only for the Neolithic Age. I don't know why you scored so little with Davidski's calc. Less than 10% Natufian does seem unusually low for people from your region.



You score very similarly to the Palestinian average, so your results are quite typical.

Looks much more better. Listen, can you do mine as well?

PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC12 ,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC22 ,PC23,PC24,PC25
Moody_scaled,0.067156,0.132019,-0.05242,-0.068153,-0.011694,-0.023427,-0.00094,-0.008538,0.004295,0.004738,-0.000974,-0.005845,0.013528,-0.003028,0.00095,0.002519,-0.002347,-0.004054,-0.003645,-0.002001,0.004866,-0.000124,0.004807,0.00012,-0.001197

PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC12 ,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC22 ,PC23,PC24,PC25
Moody,0.0059,0.013,-0.0139,-0.0211,-0.0038,-0.0084,-0.0004,-0.0037,0.0021,0.0026,-0.0006,-0.0039,0.0091,-0.0022,0.0007,0.0019,-0.0018,-0.0032,-0.0029,-0.0016,0.0039,-0.0001,0.0039,0.0001,-0.001

[Mingle]

Looks much more better. Listen, can you do mine as well?

PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC12 ,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC22 ,PC23,PC24,PC25
Moody_scaled,0.067156,0.132019,-0.05242,-0.068153,-0.011694,-0.023427,-0.00094,-0.008538,0.004295,0.004738,-0.000974,-0.005845,0.013528,-0.003028,0.00095,0.002519,-0.002347,-0.004054,-0.003645,-0.002001,0.004866,-0.000124,0.004807,0.00012,-0.001197

PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC12 ,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC22 ,PC23,PC24,PC25
Moody,0.0059,0.013,-0.0139,-0.0211,-0.0038,-0.0084,-0.0004,-0.0037,0.0021,0.0026,-0.0006,-0.0039,0.0091,-0.0022,0.0007,0.0019,-0.0018,-0.0032,-0.0029,-0.0016,0.0039,-0.0001,0.0039,0.0001,-0.001


Target: Moody
Distance: 2.8136% / 0.02813564
Aggregated
35.2 Anatolia_NF
26.8 Levant_NF
19.2 Iran_NF
14.8 Caucasus_HG
1.4 West_Siberia_HG
1.0 South_Eurasian
0.8 Eastern_HG
0.8 SSA

Weird that you get more South Eurasian (South Asia-related) than SSA. I removed the South Eurasian and ran your results again cause I thought your South Eurasian may have somehow absorbed the SSA, but your SSA stayed at 0.8%. I used Yorubas as proxy for SSA. When adding Dinkas, your SSA stayed at 0.8%.

What did Davidski give you?

[Kamal900]

Weird that you get more South Eurasian (South Asia-related) than SSA. I removed the South Eurasian and ran your results again cause I thought your South Eurasian may have somehow absorbed the SSA, but your SSA stayed at 0.8%. I used Yorubas as proxy for SSA. When adding Dinkas, your SSA stayed at 0.8%.

What did Davidski give you?

Um, what do you mean? He gave me G25 coordinates.

[Mingle]

Um, what do you mean? He gave me G25 coordinates.The results he gave you. Check post #28 on this thread.

[Abdelnour]

Pretty cool results.

Toppo, I will get with you to get my G25 results. I can pay tomorrow. I am curious on mines.

[Kamal900]

The results he gave you. Check post #28 on this thread.

Well, he only gave me the coordinates.

[Abdelnour]

Well, he only gave me the coordinates.

Cool. I have to figure out how to get the coordinates.

[Kamal900]

Not really. Its normal for calcs comprising of ancient components to get such large fits.

Also, fits below 1-1.5 are overfitting and considered bad as well.

Really? I mean, isn't fits that are below 1 considered to be very accurate?

I used unscaled coordinates using only modern samples for Palestinian Muslims:

"sample": "Test1:Palestinian",
"fit": 0.7489,
"Lebanese_Christian": 63.33,
"Egyptian": 17.5,
"BedouinB": 15,
"Dinka": 4.17,

Isn't the results accurate? Here's using ancient samples:

"sample": "Test1:Palestinian",
"fit": 0.761,
"Levant_Canaanite_MBA": 58.33,
"Levant_JOR_EBA": 19.17,
"IRN_Hajji_Firuz_BA": 13.33,
"Canary_Islands_Guanche": 5,
"TZA_Pemba_600BP": 4.17,

Here's the results for the Palestinian Muslims using scaled ancient coordinates:

"sample": "Test1:Palestinian",
"fit": 1.5156,
"Levant_Canaanite_MBA": 56.67,
"Levant_JOR_EBA": 17.5,
"Canary_Islands_Guanche": 10.83,
"TKM_IA": 6.67,
"IRN_Hajji_Firuz_BA": 5.83,
"TZA_Pemba_600BP": 2.5,

[NPKTO]

Really? I mean, isn't fits that are below 1 considered to be very accurate?

I used unscaled coordinates using only modern samples for Palestinian Muslims:

"sample": "Test1:Palestinian",
"fit": 0.7489,
"Lebanese_Christian": 63.33,
"Egyptian": 17.5,
"BedouinB": 15,
"Dinka": 4.17,

Isn't the results accurate? Here's using ancient samples:

"sample": "Test1:Palestinian",
"fit": 0.761,
"Levant_Canaanite_MBA": 58.33,
"Levant_JOR_EBA": 19.17,
"IRN_Hajji_Firuz_BA": 13.33,
"Canary_Islands_Guanche": 5,
"TZA_Pemba_600BP": 4.17,

Here's the results for the Palestinian Muslims using scaled ancient coordinates:

"sample": "Test1:Palestinian",
"fit": 1.5156,
"Levant_Canaanite_MBA": 56.67,
"Levant_JOR_EBA": 17.5,
"Canary_Islands_Guanche": 10.83,
"TKM_IA": 6.67,
"IRN_Hajji_Firuz_BA": 5.83,
"TZA_Pemba_600BP": 2.5,
If you use overlapping components, there will definitely be overfitting. You get lower fits, but the result is overfitted. For example, to model SW Asians like Palestinians using ancients, I would use Levant_N, Anatolia_N, Iran_Neolithic, CHG, and Iberomaurisian. There's some similarities between Anatolia_N and Levant_N. But these are less overlapping because Anatolia_N is significantly drifted towards WHG compared to Levant_N. I guess you could use similar idea to model with bronze age and iron age pops maybe?

[Kamal900]

If you use overlapping components, there will definitely be overfitting. You get lower fits, but the result is overfitted. For example, to model SW Asians like Palestinians using ancients, I would use Levant_N, Anatolia_N, Iran_Neolithic, CHG, and Iberomaurisian. There's some similarities between Anatolia_N and Levant_N. But these are less overlapping because Anatolia_N is significantly drifted towards WHG compared to Levant_N. I guess you could use similar idea to model with bronze age and iron age pops maybe?

What's levant_N? Do you mean Levantine Natufian or Canaanite from Syria?

[NPKTO]

What's levant_N? Do you mean Levantine Natufian or Canaanite from Syria?
It was Levantine Neolithic population. You could also replace it with Levant_PPNB (Pre Pottery Neolithic Culture B).

[Kamal900]

It was Levantine Neolithic population. You could also replace it with Levant_PPNB (Pre Pottery Neolithic Culture B).

What about CHG since it's not found in the spreadsheets?

[Mingle]

Really? I mean, isn't fits that are below 1 considered to be very accurate?

I used unscaled coordinates using only modern samples for Palestinian Muslims:

"sample": "Test1:Palestinian",
"fit": 0.7489,
"Lebanese_Christian": 63.33,
"Egyptian": 17.5,
"BedouinB": 15,
"Dinka": 4.17,

Isn't the results accurate? Here's using ancient samples:

"sample": "Test1:Palestinian",
"fit": 0.761,
"Levant_Canaanite_MBA": 58.33,
"Levant_JOR_EBA": 19.17,
"IRN_Hajji_Firuz_BA": 13.33,
"Canary_Islands_Guanche": 5,
"TZA_Pemba_600BP": 4.17,

Here's the results for the Palestinian Muslims using scaled ancient coordinates:

"sample": "Test1:Palestinian",
"fit": 1.5156,
"Levant_Canaanite_MBA": 56.67,
"Levant_JOR_EBA": 17.5,
"Canary_Islands_Guanche": 10.83,
"TKM_IA": 6.67,
"IRN_Hajji_Firuz_BA": 5.83,
"TZA_Pemba_600BP": 2.5,

If you use ancient components and you get a low fit, I'd say its pretty good. Overfitting is when genetically similar components steal from each other.

[Kamal900]

If you use ancient components and you get a low fit, I'd say its pretty good. Overfitting is when genetically similar components steal from each other.

I see. So, over-fitting is bad when using ancient samples but it's good when using modern samples like in the first results, right?

[NPKTO]

What about CHG since it's not found in the spreadsheets?
Which spreadsheet are you referring to? If you're using online nMonte runner, CHG is definitely there.

[Mingle]

I see. So, over-fitting is bad when using ancient samples but it's good when using modern samples like in the first results, right?

Yes, low distances are good when using ancient samples.

[Kamal900]

Yes, low distances are good when using ancient samples.

Wait..um, if the distance say is greater than 1.5 is good fit when using ancient samples but bad if we're using modern samples, right? I just want to get the confusion out. This is the calulcation I've done for Palestinian Muslims using ancient samples:

"sample": "Test1:Palestinian",
"fit": 2.4035,
"Levant_PPNB": 50.83,
"Kura-Araxes_ARM_Kalavan": 31.67,
"IRN_Ganj_Dareh_N": 10.83,
"TZA_Pemba_600BP": 5,
"MAR_Iberomaurusian": 1.67,
"Anatolia_Barcin_N": 0,

To you, this is great fit, right?

[Mingle]

Wait..um, if the distance say is greater than 1.5 is good fit when using ancient samples but bad if we're using modern samples, right? I just want to get the confusion out. This is the calulcation I've done for Palestinian Muslims using ancient samples:

"sample": "Test1:Palestinian",
"fit": 2.4035,
"Levant_PPNB": 50.83,
"Kura-Araxes_ARM_Kalavan": 31.67,
"IRN_Ganj_Dareh_N": 10.83,
"TZA_Pemba_600BP": 5,
"MAR_Iberomaurusian": 1.67,
"Anatolia_Barcin_N": 0,

To you, this is great fit, right?

It's not a great fit, it's okay.

For ancient samples, the lower the better. But if you get high distances using ancients, I wouldn't get too worried since genetic drift causes older samples to naturally be more distant.

For modern samples, try to keep it at around 2.

[Kamal900]

Which spreadsheet are you referring to? If you're using online nMonte runner, CHG is definitely there.

Found it. It's in Georgia category.

"sample": "Custom:Palestinian",
"fit": 3.7165,
"Levant_PPNB": 55.83,
"IRN_Wezmeh_N": 22.5,
"Anatolia_Barcin_N": 11.67,
"GEO_CHG": 10,

I think it needed more simple in the mix.

0.01
"sample": "Test1:Palestinian",
"fit": 3.666,
"Levant_PPNB": 54.17,
"IRN_Ganj_Dareh_N": 19.17,
"GEO_CHG": 12.5,
"Anatolia_Barcin_N": 8.33,
"MAR_Iberomaurusian": 5.83,

0

"sample": "Test1:Palestinian",
"fit": 3.604,
"Levant_PPNB": 52.5,
"IRN_Ganj_Dareh_N": 22.5,
"GEO_CHG": 10,
"Anatolia_Barcin_N": 9.17,
"MAR_Iberomaurusian": 5.83,

How is it now?

[Mingle]

Which region of Palestine is the OP from by the way?

[Kamal900]

It's not a great fit, it's okay.

For ancient samples, the lower the better. But if you get high distances using ancients, I wouldn't get too worried since genetic drift causes older samples to naturally be more distant.

For modern samples, try to keep it at around 2.

But..isn't 2 a high distance for the fit to be good using modern samples?

"sample": "Test1:Palestinian",
"fit": 1.3939,
"Lebanese_Christian": 65.83,
"Egyptian": 20.83,
"BedouinB": 10.83,
"Dinka": 2.5,

I don't get it. Does this look like a bad fit to you? By your statements, this is a pretty good fit for Palestinians when using only ancient samples:

"sample": "Test1:Palestinian",
"fit": 1.0421,
"Levant_Canaanite_MBA": 53.33,
"Levant_JOR_EBA": 22.5,
"TKM_IA": 13.33,
"Canary_Islands_Guanche": 6.67,
"TZA_Pemba_600BP": 4.17,
"GEO_CHG": 0,

In other words, the lesser the distance the greater the accuracy when using the ancient samples for moderns, and the greater the distance the greater the accuracy when using the modern samples for moderns?

[Kamal900]

Which region of Palestine is the OP from by the way?

The West Bank.

[Trouble]

This man is a typical Palestinian just less Arab shifted than the average.

[Kamal900]

God, you guys are making things confusing for me.

[NPKTO]

Found it. It's in Georgia category.

"sample": "Custom:Palestinian",
"fit": 3.7165,
"Levant_PPNB": 55.83,
"IRN_Wezmeh_N": 22.5,
"Anatolia_Barcin_N": 11.67,
"GEO_CHG": 10,

I think it needed more simple in the mix.

0.01
"sample": "Test1:Palestinian",
"fit": 3.666,
"Levant_PPNB": 54.17,
"IRN_Ganj_Dareh_N": 19.17,
"GEO_CHG": 12.5,
"Anatolia_Barcin_N": 8.33,
"MAR_Iberomaurusian": 5.83,

0

"sample": "Test1:Palestinian",
"fit": 3.604,
"Levant_PPNB": 52.5,
"IRN_Ganj_Dareh_N": 22.5,
"GEO_CHG": 10,
"Anatolia_Barcin_N": 9.17,
"MAR_Iberomaurusian": 5.83,

How is it now?
It looks like there's Steppe as well. Using Yamnaya lowered the fit down. CHG is not required in this model. The other model you posted is good I think.
"fit": 3.0772,
"Levant_PPNB": 54.17,
"IRN_Ganj_Dareh_N": 25,
"Anatolia_Barcin_N": 9.17,
"Yamnaya_RUS_Samara": 7.5,
"MAR_Iberomaurusian": 4.17,

[Kamal900]

It looks like there's Steppe as well. Using Yamnaya lowered the fit down. CHG is not required in this model. The other model you posted is good I think.
"fit": 3.0772,
"Levant_PPNB": 54.17,
"IRN_Ganj_Dareh_N": 25,
"Anatolia_Barcin_N": 9.17,
"Yamnaya_RUS_Samara": 7.5,
"MAR_Iberomaurusian": 4.17,

I used more recent ancient samples for the Palestinian Muslims:

"sample": "Test1alestinian",
"fit": 1.0421,
"Levant_Canaanite_MBA": 53.33,
"Levant_JOR_EBA": 22.5,
"TKM_IA": 13.33,
"Canary_Islands_Guanche": 6.67,
"TZA_Pemba_600BP": 4.17,
"GEO_CHG": 0,

According to Mingle, this is very accurate.

[NPKTO]

I used more recent ancient samples for the Palestinian Muslims:

"sample": "Test1alestinian",
"fit": 1.0421,
"Levant_Canaanite_MBA": 53.33,
"Levant_JOR_EBA": 22.5,
"TKM_IA": 13.33,
"Canary_Islands_Guanche": 6.67,
"TZA_Pemba_600BP": 4.17,
"GEO_CHG": 0,

According to Mingle, this is very accurate.
You just have to be very careful not to have multiple closely related components.

[Kamal900]

You just have to be very careful not to have multiple closely related components.

They're aren't closely related in the results, so it's good.