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Zoro
07-02-2020, 04:51 AM
The ancient DNA of two 7700-year-old women from a mountainous cave in far east Russia suggests they were closely related to the people who live in this remote and frigid corner of Asia today. The new discovery also suggests that in this region, farming spread through gradual cultural changes, rather than by an influx of farming people.

Nowadays these genomes are used as proxies for Ancient East Asian ancestry. Out of curiousity I took the highest 2 coverage samples and ran them through Plink's IBS program to see who they are genetically closer to.

I don't have samples from all Siberian populations but out of the samples I have here are the results Devil-Gate sample NEO236:

1- Closest is the ancient Devils-Gate Neo240 sample. From moderns they are closest to modern Japanese followed by other E. Asians.

2- They are furthest from Africans.

3- After E. Asians come northern S. Asians and Central Asian Tajiks.

4- Following these are W. Asians with Kurds and some Caucasians closest and Bedouin, Assyrians and S. Iranians furthest.

5- Following W. Asians come Europeans with Finns on top and Sardinians on bottom.

6- From the highest quality ancient genomes I have Botai is closest and Stuttgart-EEF is furthest.



Over the next few days I'll do similar runs for EEF, WHG, Eastern Yamnaya, Botai and S/SC Asians.


<colgroup width="57"></colgroup> <colgroup width="144"></colgroup> <colgroup width="121"></colgroup> <colgroup width="243"></colgroup> <colgroup width="132" span="2"></colgroup> <tbody>
NO
FID1
IID1
FID2
IID2
DISTANCE


1
DevilsCave-N
NEO236
DevilsCave-N
NEO240
0.82125


2
DevilsCave-N
NEO236
Japanese
S-Japanese-1
0.80418


3
DevilsCave-N
NEO236
Japanese
S-Japanese-3
0.80361


4
DevilsCave-N
NEO236
Japanese
S-Japanese-2
0.80333


5
DevilsCave-N
NEO236
Mongola
S-Mongola-2
0.80324


6
DevilsCave-N
NEO236
Han
S-Han-1
0.80306


7
DevilsCave-N
NEO236
Mongola
S-Mongola-1
0.80272


8
DevilsCave-N
NEO236
Yakut
S-Yakut-2
0.80206


9
DevilsCave-N
NEO236
Han
S-Han-2
0.80201


10
DevilsCave-N
NEO236
Buryat
Buryats2
0.80195


11
DevilsCave-N
NEO236
Han
B-Han-3
0.80099


12
DevilsCave-N
NEO236
Yakut
S-Yakut-1
0.80054


13
DevilsCave-N
NEO236
Kalmyk
Kalmyks2
0.80011


14
DevilsCave-N
NEO236
Buryat
Buryats1
0.79995


15
DevilsCave-N
NEO236
Dai
B-Dai-4
0.79974


16
DevilsCave-N
NEO236
Kalmyk
Kalmyks1
0.79930


17
DevilsCave-N
NEO236
Dai
A-Dai-5
0.79923


18
DevilsCave-N
NEO236
Karitiana
BI16
0.79861


19
DevilsCave-N
NEO236
China-Lahu
S-Lahu-2
0.79861


20
DevilsCave-N
NEO236
Dai
S-Dai-1
0.79853


21
DevilsCave-N
NEO236
China-Lahu
S-Lahu-1
0.79827


22
DevilsCave-N
NEO236
Dai
S-Dai-2
0.79790


23
DevilsCave-N
NEO236
Karitiana
S-Karitiana-2
0.79568


24
DevilsCave-N
NEO236
Karitiana
B-Karitiana-3
0.79503


25
DevilsCave-N
NEO236
Karitiana
S-Karitiana-1
0.79496


26
DevilsCave-N
NEO236
Kazakh
Kazakhs2
0.79412


27
DevilsCave-N
NEO236
Kazakh
Kazkahs1
0.79322


28
DevilsCave-N
NEO236
Karakalpak
Karakalpaks2
0.79193


29
DevilsCave-N
NEO236
Kazakh
Kazakhs3
0.79134


30
DevilsCave-N
NEO236
Karakalpak
Karakalpaks3
0.79127


31
DevilsCave-N
NEO236
Karakalpak
Karakalpaks1
0.78937


32
DevilsCave-N
NEO236
Uyghur
Uyghurs2
0.78922


33
DevilsCave-N
NEO236
Turkmen
Turkmens2
0.78824


34
DevilsCave-N
NEO236
Uyghur
Uyghurs1
0.78803


35
DevilsCave-N
NEO236
Uzbek
Uzbeks2
0.78788


36
DevilsCave-N
NEO236
Uyghur
Uyghurs3
0.78778


37
DevilsCave-N
NEO236
Uyghur
S-Uygur-1
0.78744


38
DevilsCave-N
NEO236
Tatar-Tomsk
TomskTatars2
0.78728


39
DevilsCave-N
NEO236
Tatar-Tomsk
TomskTatars1
0.78721


40
DevilsCave-N
NEO236
Uzbek
Uzbeks1
0.78721


41
DevilsCave-N
NEO236
Bashkir
Bashkirs2
0.78658


42
DevilsCave-N
NEO236
Uyghur
S-Uygur-2
0.78591


43
DevilsCave-N
NEO236
Tajik
Tajiks1
0.78323


44
DevilsCave-N
NEO236
Tajik-Tajikistan
Tajik-Tajikistan
0.78311


45
DevilsCave-N
NEO236
Uzbek
Uzbeks3
0.78301


46
DevilsCave-N
NEO236
Turkmen
Turkmens1
0.78266


47
DevilsCave-N
NEO236
Bashkir
Bashkirs1
0.78185


48
DevilsCave-N
NEO236
Bashkir
Bashkirs3
0.78091


49
DevilsCave-N
NEO236
Kapu
S-Kapu-2
0.78073


50
DevilsCave-N
NEO236
Kazakhstan-Botai
BOT15
0.78040


51
DevilsCave-N
NEO236
Kapu
S-Kapu-1
0.77917


52
DevilsCave-N
NEO236
Punjabi
S-Punjabi-2
0.77906


53
DevilsCave-N
NEO236
Punjabi
S-Punjabi-1
0.77904


54
DevilsCave-N
NEO236
Tatar-Volga
VolgaTatars1
0.77875


55
DevilsCave-N
NEO236
Punjabi
S-Punjabi-3
0.77837


56
DevilsCave-N
NEO236
Punjabi-Pk
Punjabi-Pk
0.77820


57
DevilsCave-N
NEO236
Tajik
Tadjik
0.77799


58
DevilsCave-N
NEO236
Tatar-Volga
VolgaTatars2
0.77799


59
DevilsCave-N
NEO236
Tajik
Tajiks3
0.77787


60
DevilsCave-N
NEO236
Punjabi-Pk
Punjabi-Pk
0.77736


61
DevilsCave-N
NEO236
Punjabi-IN
Punjabi-IN
0.77677


62
DevilsCave-N
NEO236
Kalash
S-Kalash-2
0.77647


63
DevilsCave-N
NEO236
Sindhi
S-Sindhi-2
0.77626


64
DevilsCave-N
NEO236
Punjabi-Arain
Punjabi-Arain
0.77601


65
DevilsCave-N
NEO236
Sindhi
S-Sindhi-1
0.77595


66
DevilsCave-N
NEO236
Pashtun-Pak
Pashtun-Pak
0.77580


67
DevilsCave-N
NEO236
Pashtun-Afg
Pashtun-Afg
0.77578


68
DevilsCave-N
NEO236
Punjabi-Pk
Punjabi-Pk
0.77561


69
DevilsCave-N
NEO236
Punjabi-Gujjar
Punjabi-Gujjar
0.77554


70
DevilsCave-N
NEO236
Punjabi
S-Punjabi-4
0.77548


71
DevilsCave-N
NEO236
Pashtun-Afg
Pashtun-Afg
0.77542


72
DevilsCave-N
NEO236
Kurd-Kurmanji-IQ
Kurd-Kurmanji-IQ
0.77533


73
DevilsCave-N
NEO236
Pathan
S-Pathan-1
0.77531


74
DevilsCave-N
NEO236
Pashtun-Pak
Pashtun-Pak
0.77490


75
DevilsCave-N
NEO236
Kalash
S-Kalash-1
0.77472


76
DevilsCave-N
NEO236
Adygei
S-Adygei-1
0.77470


77
DevilsCave-N
NEO236
Pathan
S-Pathan-2
0.77469


78
DevilsCave-N
NEO236
Balochi
S-Balochi-2
0.77434


79
DevilsCave-N
NEO236
Tajik
S-Tajik-1
0.77409


80
DevilsCave-N
NEO236
Brahui
S-Brahui-2
0.77393


81
DevilsCave-N
NEO236
Russia-N-Ossetian
S-North-Ossetian-1
0.77348


82
DevilsCave-N
NEO236
Tajik
S-Tajik-2
0.77344


83
DevilsCave-N
NEO236
Turkish
S-Turkish-2
0.77324


84
DevilsCave-N
NEO236
Kurd-Kurmanji-IQ
Kurd-Kurmanji-IQ
0.77311


85
DevilsCave-N
NEO236
Kurd-Feyli
Kurd-Feyli
0.77300


86
DevilsCave-N
NEO236
Brahui
S-Brahui-1
0.77296


87
DevilsCave-N
NEO236
Kurd-Kurmanji-IQ
Kurd-Kurmanji-IQ
0.77252


88
DevilsCave-N
NEO236
Makrani
S-Makrani-1
0.77233


89
DevilsCave-N
NEO236
Kazakhstan-EBA-Yamnaya
Yamnaya
0.77232


90
DevilsCave-N
NEO236
Iranian
Iranian
0.77232


91
DevilsCave-N
NEO236
Adygei
S-Adygei-2
0.77227


92
DevilsCave-N
NEO236
Turkish
S-Turkish-1
0.77206


93
DevilsCave-N
NEO236
Balochi
S-Balochi-1
0.77204


94
DevilsCave-N
NEO236
Finnish
S-Finnish-1
0.77203


95
DevilsCave-N
NEO236
Finnish
S-Finnish-2
0.77172


96
DevilsCave-N
NEO236
Baloch-IR
Baloch-IR
0.77148


97
DevilsCave-N
NEO236
Turkish
Turkish
0.77147


98
DevilsCave-N
NEO236
Kurd-Feyli
Kurd-Feyli
0.77131


99
DevilsCave-N
NEO236
Iranian
S-Iranian-2
0.77126


100
DevilsCave-N
NEO236
Iranian
S-Iranian-1
0.77125


101
DevilsCave-N
NEO236
Estonian
S-Estonian-2
0.77121


102
DevilsCave-N
NEO236
Kurd-Turkey
Kurd-Turkey
0.77094


103
DevilsCave-N
NEO236
Kurd-Feyli
Kurd-Feyli
0.77074


104
DevilsCave-N
NEO236
Makrani
S-Makrani-2
0.77070


105
DevilsCave-N
NEO236
Lezgin
S-Lezgin-1
0.77066


106
DevilsCave-N
NEO236
Lezgin
S-Lezgin-2
0.77062


107
DevilsCave-N
NEO236
Armenian
S-Armenian-1
0.77053


108
DevilsCave-N
NEO236
Georgian
S-Georgian-2
0.77008


109
DevilsCave-N
NEO236
Baloch-IR
Baloch-IR
0.76992


110
DevilsCave-N
NEO236
Kurd-Feyli
Kurd-Feyli
0.76988


111
DevilsCave-N
NEO236
Finnish
S-Finnish-3
0.76986


112
DevilsCave-N
NEO236
Georgian
S-Georgian-1
0.76955


113
DevilsCave-N
NEO236
English
S-English-1
0.76944


114
DevilsCave-N
NEO236
Estonian
S-Estonian-1
0.76941


115
DevilsCave-N
NEO236
Armenian
S-Armenian-2
0.76938


116
DevilsCave-N
NEO236
Hungarian
S-Hungarian-1
0.76907


117
DevilsCave-N
NEO236
Iranian
Iranian
0.76906


118
DevilsCave-N
NEO236
Basque
S-Basque-1
0.76888


119
DevilsCave-N
NEO236
Assyrian
Assyrian
0.76876


120
DevilsCave-N
NEO236
Assyrian
Assyrian
0.76875


121
DevilsCave-N
NEO236
Hungarian
S-Hungarian-2
0.76871


122
DevilsCave-N
NEO236
Spanish
S-Spanish-1
0.76857


123
DevilsCave-N
NEO236
Spanish
S-Spanish-2
0.76829


124
DevilsCave-N
NEO236
Basque
S-Basque-2
0.76828


125
DevilsCave-N
NEO236
English
S-English-2
0.76800


126
DevilsCave-N
NEO236
BedouinB
S-BedouinB-2
0.76752


127
DevilsCave-N
NEO236
Sardinian
S-Sardinian-2
0.76716


128
DevilsCave-N
NEO236
Sardinian
S-Sardinian-1
0.76702


129
DevilsCave-N
NEO236
Loschbour-WHG
Loschbour-snpAD
0.76663


130
DevilsCave-N
NEO236
Sardinian
B-Sardinian-3
0.76662


131
DevilsCave-N
NEO236
Stuttgart-EEF
Stuttgart-published
0.76585


132
DevilsCave-N
NEO236
BedouinB
S-BedouinB-1
0.76549


133
DevilsCave-N
NEO236
Somali
S-Somali-1
0.74463


134
DevilsCave-N
NEO236
Masai
S-Masai-1
0.73893


135
DevilsCave-N
NEO236
Masai
S-Masai-2
0.73745


136
DevilsCave-N
NEO236
Luhya
S-Luhya-2
0.72884


137
DevilsCave-N
NEO236
Luhya
S-Luhya-1
0.72868


138
DevilsCave-N
NEO236
Mbuti
S-Mbuti-3
0.72837


139
DevilsCave-N
NEO236
Yoruba
S-Yoruba-1
0.72825


140
DevilsCave-N
NEO236
Mbuti
S-Mbuti-2
0.72789


141
DevilsCave-N
NEO236
Yoruba
S-Yoruba-2
0.72671


142
DevilsCave-N
NEO236
Yoruba
B-Yoruba-3
0.72566

</tbody>
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Zoro
07-02-2020, 03:15 PM
Out of curiosity I went to Vahuado site to see if the G25 results also make sense for Devils-Gate-N. Unfortunately the G25 results were NONSENSICAL as you can see below.

You don't have to take my word for it. Just go to Vahuado and copy Devils-Gate from G25 SCALED AVG Ancient spreadsheet and paste it in TARGET in G25 SCALED AVG Moderns calculator.

Hopefully this will convince those who are still on the fence to not take the G25 outputs seriously.

Here are some G25 nonsensical results compared to my PLINK IBS results above. You maybe able to spot even more illogical results.


<colgroup width="72"></colgroup> <colgroup width="365"></colgroup> <colgroup width="116"></colgroup> <colgroup width="153"></colgroup> <tbody>
LIST OF G25 NONSENSICAL RESULTS


NO
NONSENSICAL RESULT
IBS- PLINK
DAVIDSKI – G25


1
Devils-Gate closer to many S.& W Asians & Europeans than to E. Eurasians
NO
YES


2
Devils-Gate closer to Libyans, Algerians, Egyptians, Berber than to Lithuanians & Armenians
NO
YES


3
Devils-Gate closer to S. Iranians than to Kurds
NO
YES

</tbody>



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<colgroup width="165"></colgroup> <colgroup width="280"></colgroup> <tbody>
G25 Modern Averages scaled, official datasheet


POPULATION
Distance to RUS_Devils_Gate_Cave_N


Mongola
0.09648


Korean
0.12362


Japanese
0.12374


Tibetan_Gangcha
0.12467


Kalmyk
0.13047


Mongolian
0.13589


Buryat
0.13749


Han_Jiangsu
0.15949


Han_Shanghai
0.16224


Han_Zhejiang
0.16848


Han_Hubei
0.17012


Han_Sichuan
0.17243


Koryak
0.18688


Yakut
0.19216


Dai
0.24433


Kazakh
0.24489


Brahmin_Manipuri
0.28047


Karakalpak
0.28056


Uygur
0.31489


Uzbek
0.36435


Bashkir
0.37197


Turkmen
0.42475


Gond
0.42698


Paniya
0.45062


Irula
0.45444


Pulliyar
0.45849


Burusho
0.46823


North_Kannadi
0.46981


Hakkipikki
0.47077


Uttar_Pradesh
0.47749


Mala
0.47761


Yadava
0.47845


Maratha
0.47910


Dusadh
0.47939


Kol
0.48416


Tatar_Kazan
0.48508


Piramalai
0.48621


Kanjar
0.48656


Punjabi_Lahore
0.48694


Mixtec
0.48810


Zapotec
0.48925


Pima
0.48936


Velamas
0.49030


Brahmin_Tamil_Nadu
0.49132


Tajik
0.49203


Gujarati
0.49562


Kashmiri_Pandit
0.49853


Mayan
0.49890


Mixe
0.49892


Quechua
0.50299


Brahmin_Gujarat
0.50491


Brahmin_Uttar_Pradesh
0.50595


Tatar_Mishar
0.51283


Pashtun
0.51377


Tajik_Ishkashim
0.51603


Gujar_Pakistan
0.51798


Sindhi
0.51821


Punjabi_Jatt
0.51933


Pashtun-Yusufzai
0.52017


Pashtun-Uthmankhel
0.52148


Tajik_Shugnan
0.52207


Bolivian_LaPaz
0.52214


Pashtun-Tarkalani
0.52294


Tajik_Rushan
0.52785


Kalash
0.52873


Brahui
0.54727


Balochi
0.54963


Parsi_India
0.55047


Parsi_Pakistan
0.55150


Makrani
0.55650


Circassian
0.55678


Iranian_Bandari
0.55968


North_Ossetian
0.56144


Finnish_East
0.56274


Karitiana
0.56404


Iranian_Fars
0.57057


Surui
0.57266


Finnish
0.57687


Adygei
0.57706


Australian
0.57981


Iranian_Lor
0.58065


Tabasaran
0.58172


Iranian_Zoroastrian
0.58288


Kurdish
0.58813


Syrian
0.59025


Abkhasian
0.59109


Jordanian
0.59519


Russian_Kursk
0.59637


Moldovan
0.59668


Libyan
0.59770


BedouinA
0.59798


Russian_Orel
0.59873


Egyptian
0.59881


Algerian
0.60187


Estonian
0.60205


Berber_Tunisia_Sen
0.60223


Hungarian
0.60227


Belarusian
0.60644


Albanian
0.60646


Armenian
0.60886


Spanish_Asturias
0.61105


Spanish_Andalucia
0.61165


Lithuanian_RA
0.61167


Spanish_Galicia
0.61185


Spanish_Soria
0.61193


English
0.61247


Lithuanian_SZ
0.61545


Sardinian
0.63860


Somali
0.65247


Masai
0.71578


Papuan
0.75843


Ethiopian_Gumuz
0.75873


Ethiopian_Mursi
0.76359


Ethiopian_Anuak
0.79354


Luhya_Kenya
0.80931


Yoruba
0.83579


Mbuti
1.00219

</tbody>
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vbnetkhio
07-02-2020, 03:22 PM
The ancient DNA of two 7700-year-old women from a mountainous cave in far east Russia suggests they were closely related to the people who live in this remote and frigid corner of Asia today. The new discovery also suggests that in this region, farming spread through gradual cultural changes, rather than by an influx of farming people.

Nowadays these genomes are used as proxies for Ancient East Asian ancestry. Out of curiousity I took the highest 2 coverage samples and ran them through Plink's IBS program to see who they are genetically closer to.

I don't have samples from all Siberian populations but out of the samples I have here are the results Devil-Gate sample NEO236:

1- Closest is the ancient Devils-Gate Neo240 sample. From moderns they are closest to modern Japanese followed by other E. Asians.

2- They are furthest from Africans.

3- After E. Asians come northern S. Asians and Central Asian Tajiks.

4- Following these are W. Asians with Kurds and some Caucasians closest and Bedouin, Assyrians and S. Iranians furthest.

5- Following W. Asians come Europeans with Finns on top and Sardinians on bottom.

6- From the highest quality ancient genomes I have Botai is closest and Stuttgart-EEF is furthest.



Over the next few days I'll do similar runs for EEF, WHG, Eastern Yamnaya, Botai and S/SC Asians.


is IBS similar to FST?
Zoro
07-02-2020, 03:35 PM
is IBS similar to FST?

yes it's similar but I think that the plink --genome flag is more useful because it also outputs IBD. Pi-Hat, Z2, Z1, Z0 and PPC are really useful if you're trying to figure out more recent admixture

It's pretty simple you can use:

/plink --bfile test --genome
Zoro
07-02-2020, 03:48 PM
Based on the above G25 illogical results for Devils-Gate-N how can anyone trust the G25 ancient models or distances
Kyp
07-02-2020, 03:55 PM
Target: FatherKyp
Distance: 1.5896% / 0.01589648
31.6 Anatolia_Barcin_N
23.8 IRN_Ganj_Dareh_N
18.8 Yamnaya_RUS_Samara
10.4 RUS_Devils_Gate_Cave_N
8.6 GEO_CHG
6.8 Levant_Natufian
Zoro
07-02-2020, 04:05 PM
Target: FatherKyp
Distance: 1.5896% / 0.01589648
31.6 Anatolia_Barcin_N
23.8 IRN_Ganj_Dareh_N
18.8 Yamnaya_RUS_Samara
10.4 RUS_Devils_Gate_Cave_N
8.6 GEO_CHG
6.8 Levant_Natufian

I expect your dad to score Devils-Gate-N because that't the ancient proxy but what I'm saying is that if the G25 distances are screwed up for Devils-Gate (above table) then it's likely the distances for the other ancients are screwed up too in the G25 which means the percentages in your dad's model are screwed up.

I'm planning to do a comparison of G25 against Plink IBS for some of the other high quality ancients such as Stuttgart, Loschbour, Botai, Yamnaya so we can have a better idea how screwed up the G25 is. I remember the nMonte designer Hudjbrets wrote in the readme file Garbage in --> Garbage out lol.
vbnetkhio
07-02-2020, 04:11 PM
Based on the above G25 illogical results for Devils-Gate-N how can anyone trust the G25 ancient models or distances

the proper tools are too complicated for the average user and require a lot of ram and processing power
Zoro
07-02-2020, 04:24 PM
the proper tools are too complicated for the average user and require a lot of ram and processing power

I agree but it’s annoying to see how users who don’t know better blindly put faith in Davidski G25 as if it’s the gospel when we can see it’s quite off.

Actually plink by itself without using Admixture doesn’t take much time to process and a good dataset is only about 1 gig



Edit: It would get complicated as you say if they have to use Admixtools to convert dataset to plink but if they can find a dataset in bed bim fam format and only use plink then it’s not too bad but they would have to know how to do QC on dataset and work with Linux
vbnetkhio
07-02-2020, 04:42 PM
I agree but it’s annoying to see how users who don’t know better blindly put faith in Davidski G25 as if it’s the gospel when we can see it’s quite off.

Actually plink by itself without using Admixture doesn’t take much time to process and a good dataset is only about 1 gig

but in plink you can't use outgroups, right?
i'm interested in comparing BA and IA samples to moderns, and qpAdm is perfect for this.
because i can include that ancient stuff like WHG, EEF etc. as outgroups, and then the algorithm actually comapres the BA onwards drift
Zoro
07-02-2020, 04:58 PM
......
Zoro
07-02-2020, 05:04 PM
..........
Zoro
07-02-2020, 05:06 PM
but in plink you can't use outgroups, right?
i'm interested in comparing BA and IA samples to moderns, and qpAdm is perfect for this.
because i can include that ancient stuff like WHG, EEF etc. as outgroups, and then the algorithm actually comapres the BA onwards drift

Yes but you can do good work in plink if you do this:

1- Prune your dataset for QC so that no sample has any missing genotype: /plink --bfile Reich_set --keep a.txt --geno 0.005 --make-bed --out Test

2- Check to make sure no sample as missing genotype: /plink --bfile Test --missing. You'll get a report of how many SNPs each sample is missing

3- To remove common alleles common to Africans and Eurasians : /plink --bfile Test --max-maf 0.25 --make-bed --out Test1. This will get rid of allleles with MAF>25%

4- /plink --bfile Test1 --genome. You'll get a text file with distances, IBD Z2, Z1, Z0, Pi-Hat, PPC which is really good.
Zoro
07-02-2020, 05:59 PM
Out of curiosity I went to Vahuado site to see if the G25 results also make sense for Devils-Gate-N. Unfortunately the G25 results were NONSENSICAL as you can see below.

You don't have to take my word for it. Just go to Vahuado and copy Devils-Gate from G25 SCALED AVG Ancient spreadsheet and paste it in TARGET in G25 SCALED AVG Moderns calculator.

Hopefully this will convince those who are still on the fence to not take the G25 outputs seriously.

Here are some G25 nonsensical results compared to my PLINK IBS results above. You maybe able to spot even more illogical results.


<colgroup width="72"></colgroup> <colgroup width="365"></colgroup> <colgroup width="116"></colgroup> <colgroup width="153"></colgroup> <tbody>
LIST OF G25 NONSENSICAL RESULTS


NO
NONSENSICAL RESULT
IBS- PLINK
DAVIDSKI – G25


1
Devils-Gate closer to many S.& W Asians & Europeans than to E. Eurasians
NO
YES


2
Devils-Gate closer to Libyans, Algerians, Egyptians, Berber than to Lithuanians & Armenians
NO
YES


3
Devils-Gate closer to S. Iranians than to Kurds
NO
YES

</tbody>



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<colgroup width="165"></colgroup> <colgroup width="280"></colgroup> <tbody>
G25 Modern Averages scaled, official datasheet


POPULATION
Distance to RUS_Devils_Gate_Cave_N


Mongola
0.09648


Korean
0.12362


Japanese
0.12374


Tibetan_Gangcha
0.12467


Kalmyk
0.13047


Mongolian
0.13589


Buryat
0.13749


Han_Jiangsu
0.15949


Han_Shanghai
0.16224


Han_Zhejiang
0.16848


Han_Hubei
0.17012


Han_Sichuan
0.17243


Koryak
0.18688


Yakut
0.19216


Dai
0.24433


Kazakh
0.24489


Brahmin_Manipuri
0.28047


Karakalpak
0.28056


Uygur
0.31489


Uzbek
0.36435


Bashkir
0.37197


Turkmen
0.42475


Gond
0.42698


Paniya
0.45062


Irula
0.45444


Pulliyar
0.45849


Burusho
0.46823


North_Kannadi
0.46981


Hakkipikki
0.47077


Uttar_Pradesh
0.47749


Mala
0.47761


Yadava
0.47845


Maratha
0.47910


Dusadh
0.47939


Kol
0.48416


Tatar_Kazan
0.48508


Piramalai
0.48621


Kanjar
0.48656


Punjabi_Lahore
0.48694


Mixtec
0.48810


Zapotec
0.48925


Pima
0.48936


Velamas
0.49030


Brahmin_Tamil_Nadu
0.49132


Tajik
0.49203


Gujarati
0.49562


Kashmiri_Pandit
0.49853


Mayan
0.49890


Mixe
0.49892


Quechua
0.50299


Brahmin_Gujarat
0.50491


Brahmin_Uttar_Pradesh
0.50595


Tatar_Mishar
0.51283


Pashtun
0.51377


Tajik_Ishkashim
0.51603


Gujar_Pakistan
0.51798


Sindhi
0.51821


Punjabi_Jatt
0.51933


Pashtun-Yusufzai
0.52017


Pashtun-Uthmankhel
0.52148


Tajik_Shugnan
0.52207


Bolivian_LaPaz
0.52214


Pashtun-Tarkalani
0.52294


Tajik_Rushan
0.52785


Kalash
0.52873


Brahui
0.54727


Balochi
0.54963


Parsi_India
0.55047


Parsi_Pakistan
0.55150


Makrani
0.55650


Circassian
0.55678


Iranian_Bandari
0.55968


North_Ossetian
0.56144


Finnish_East
0.56274


Karitiana
0.56404


Iranian_Fars
0.57057


Surui
0.57266


Finnish
0.57687


Adygei
0.57706


Australian
0.57981


Iranian_Lor
0.58065


Tabasaran
0.58172


Iranian_Zoroastrian
0.58288


Kurdish
0.58813


Syrian
0.59025


Abkhasian
0.59109


Jordanian
0.59519


Russian_Kursk
0.59637


Moldovan
0.59668


Libyan
0.59770


BedouinA
0.59798


Russian_Orel
0.59873


Egyptian
0.59881


Algerian
0.60187


Estonian
0.60205


Berber_Tunisia_Sen
0.60223


Hungarian
0.60227


Belarusian
0.60644


Albanian
0.60646


Armenian
0.60886


Spanish_Asturias
0.61105


Spanish_Andalucia
0.61165


Lithuanian_RA
0.61167


Spanish_Galicia
0.61185


Spanish_Soria
0.61193


English
0.61247


Lithuanian_SZ
0.61545


Sardinian
0.63860


Somali
0.65247


Masai
0.71578


Papuan
0.75843


Ethiopian_Gumuz
0.75873


Ethiopian_Mursi
0.76359


Ethiopian_Anuak
0.79354


Luhya_Kenya
0.80931


Yoruba
0.83579


Mbuti
1.00219

</tbody>
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If anyone is interested in reading the paper on Devils-Gate-N it's here https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5287702/. It also shows Devil-Gates closer to Japanese than Mongols like my Plink IBS run and unlike the G25
Zoro
07-07-2020, 02:51 PM
..........
Voskos
07-07-2020, 02:54 PM
WHG, Bedouins and Sardinians the furthest away from it as expected.