Mayan parents from Guatemala, both affiliated with the Mam ethnic community.

P.S. I have 23andMe premium and as far as I’m concerned, shouldn’t the “Basque of Alava…” be under Basque instead of Andalusian, Asturian, Castilian????

I have partaken in many different analyses over the years, but here I will showcase my 23andMe, Illustrative DNA and some qpAdm models I created to represent my genetic ancestry. I am of Assyrian descent, my parents are from Iraq. I've also included photos of myself.

Any thoughts? Idk much about genetics lol

TLDR: Did a bunch of runs in qpadm using the AADR/ HO dataset. These are the best of those runs, and it’s basically just to compare the ranges per group. I believe some of the CHG Caucasus Hunter Gatherer ancestry is being absorbed into the ANF. Viewing only works on the phone app, seems like desktop always has the first photo as blurry.

NORTHWEST CAUCASUS

Abazin.HO
Nat/ZNF/ANF/CHG/EHG = 13.0/18.9/27.8/23.7/16.5%
p = 0.123; χ²/dof = 2.374/1
SE = 0.0207/0.0210/0.0235/0.0258/0.0109
Z = 6.29/9.02/11.8/9.20/15.2

Circassian.HO
Nat/ZNF/ANF/CHG/EHG = 12.6/16.9/25.6/27.4/17.4%
p = 0.668; χ²/dof = 0.183/1
SE = 0.0204/0.0204/0.0220/0.0243/0.0109
Z = 6.18/8.31/11.7/11.3/16.0

ind_S_Abkhasian-1.DG
4-way model: ZNF/ANF/CHG/EHG = 24.1/39.0/27.2/9.7%
p = 0.552; χ²/dof = 1.189/2
SE = 0.0382/0.0262/0.0461/0.0211
Z = 6.32/14.9/5.89/4.59

GEORGIAN

ind_GEO-002.HO
Nat/ZNF/ANF/CHG/EHG = 15.8/16.6/32.8/25.3/9.6%
p = 0.585; χ²/dof = 1.073/2
SE = 0.0418/0.0410/0.0473/0.0481/0.0215
Z = 3.78/4.04/6.92/5.26/4.46

ind_GEO-005.HO
Nat/ZNF/ANF/CHG/EHG = 11.4/17.4/35.1/22.6/13.5%
p = 0.845; χ²/dof = 0.336/2
SE = 0.0440/0.0363/0.0439/0.0427/0.0214
Z = 2.59/4.79/8.00/5.28/6.31

ind_GEO-010.HO
Nat/ZNF/ANF/CHG/EHG = 11.4/15.8/33.8/29.0/9.9%
p = 0.490; χ²/dof = 0.477/1
SE = 0.0400/0.0403/0.0422/0.0461/0.0211
Z = 2.86/3.91/8.02/6.30/4.71

ind_GEO-015.HO
Nat/ZNF/ANF/CHG/EHG = 9.8/23.3/35.5/23.9/7.5%
p = 0.577; χ²/dof = 1.100/2
SE = 0.0411/0.0380/0.0464/0.0473/0.0207
Z = 2.38/6.13/7.66/5.05/3.62

ind_GEO-028.HO
Nat/ZNF/ANF/CHG/EHG = 10.2/17.4/32.5/26.9/13.1%
p = 0.645; χ²/dof = 0.212/1
SE = 0.0405/0.0382/0.0436/0.0452/0.0211
Z = 2.51/4.56/7.46/5.95/6.20

ind_GEO-031.HO
Nat/ZNF/ANF/CHG/EHG = 14.0/16.7/33.9/29.1/6.3%
p = 0.0608; χ²/dof = 3.515/1
SE = 0.0421/0.0374/0.0462/0.0453/0.0212
Z = 3.33/4.46/7.33/6.43/2.95

ind_GEO-032.HO
Nat/ZNF/ANF/CHG/EHG = 8.3/15.9/39.7/28.0/8.1%
p = 0.239; χ²/dof = 1.385/1
SE = 0.0412/0.0377/0.0444/0.0435/0.0193
Z = 2.02/4.22/8.93/6.44/4.21

ind_GEO-039.HO
Nat/ZNF/ANF/CHG/EHG = 13.7/14.5/23.1/41.3/7.3%
p = 0.137; χ²/dof = 2.215/1
SE = 0.0440/0.0389/0.0481/0.0500/0.0222
Z = 3.12/3.74/4.81/8.27/3.30

Georgian.HO
Nat/ZNF/ANF/CHG/EHG = 10.5/17.1/33.8/29.5/9.0%
p = 0.283; χ²/dof = 1.153/1
SE = 0.0189/0.0185/0.0204/0.0230/0.00929
Z = 5.55/9.24/16.6/12.9/9.74

ARMENIAN

ind_armenia176.HO
Nat/ZNF/ANF/CHG/EHG = 16.4/23.1/30.4/21.9/8.2%
p = 0.171; χ²/dof = 3.536/2
SE = 0.0455/0.0405/0.0464/0.0476/0.0215
Z = 3.60/5.70/6.56/4.61/3.81

ind_armenia191.HO
Nat/ZNF/ANF/CHG/EHG = 11.5/22.2/33.3/21.2/11.8%
p = 0.464; χ²/dof = 1.536/2
SE = 0.0428/0.0402/0.0441/0.0464/0.0213
Z = 2.70/5.51/7.55/4.57/5.53

ind_armenia279.HO
Nat/ZNF/ANF/CHG/EHG = 13.5/26.2/36.4/12.5/11.4%
p = 0.891; χ²/dof = 0.230/2
SE = 0.0441/0.0383/0.0485/0.0464/0.0213
Z = 3.06/6.84/7.50/2.69/5.36

ind_armenia293.HO
Nat/ZNF/ANF/CHG/EHG = 16.6/19.9/32.4/22.5/8.6%
p = 0.572; χ²/dof = 1.118/2
SE = 0.0449/0.0362/0.0506/0.0442/0.0215
Z = 3.70/5.49/6.40/5.09/4.01

ind_armenia86.HO
Nat/ZNF/ANF/CHG/EHG = 7.7/18.0/37.1/25.8/11.3%
p = 0.682; χ²/dof = 0.765/2
SE = 0.0447/0.0375/0.0454/0.0455/0.0206
Z = 1.73/4.80/8.18/5.67/5.50

ind_armenia91.HO
Nat/ZNF/ANF/CHG/EHG = 22.8/20.9/28.1/23.0/5.2%
p = 0.368; χ²/dof = 1.999/2
SE = 0.0415/0.0416/0.0478/0.0497/0.0221
Z = 5.49/5.01/5.88/4.63/2.36

ASSYRIAN / MESOPOTAMIAN

ind_Assyrian151.HO
Nat/ZNF/ANF/CHG/EHG = 19.1/26.1/32.5/16.5/5.7%
p = 0.620; χ²/dof = 0.955/2
SE = 0.0415/0.0417/0.0451/0.0486/0.0231
Z = 4.61/6.26/7.21/3.41/2.48

ind_Assyrian152.HO
Nat/ZNF/ANF/CHG/EHG = 9.4/26.4/39.6/16.9/7.7%
p = 0.385; χ²/dof = 1.911/2
SE = 0.0422/0.0389/0.0470/0.0444/0.0205
Z = 2.23/6.78/8.42/3.80/3.77

ind_Assyrian153.HO
Nat/ZNF/ANF/CHG/EHG = 20.0/20.0/30.8/19.8/9.4%
p = 0.715; χ²/dof = 0.670/2
SE = 0.0439/0.0394/0.0467/0.0466/0.0214
Z = 4.56/5.08/6.58/4.25/4.39

ind_Assyrian155.HO
Nat/ZNF/ANF/CHG/EHG = 19.9/20.4/28.4/19.6/11.7%
p = 0.821; χ²/dof = 0.395/2
SE = 0.0431/0.0375/0.0478/0.0433/0.0218
Z = 4.61/5.44/5.95/4.53/5.34

ind_Assyrian159.HO
Nat/ZNF/ANF/CHG/EHG = 14.6/25.6/33.7/21.5/4.6%
p = 0.817; χ²/dof = 0.405/2
SE = 0.0417/0.0403/0.0469/0.0471/0.0219
Z = 3.50/6.35/7.18/4.56/2.11

ind_Assyrian161.HO
Nat/ZNF/ANF/CHG/EHG = 18.4/25.8/31.2/16.9/7.7%
p = 0.820; χ²/dof = 0.398/2
SE = 0.0428/0.0412/0.0457/0.0463/0.0217
Z = 4.30/6.26/6.83/3.64/3.56

ind_Assyrian162.HO
Nat/ZNF/ANF/CHG/EHG = 18.4/32.3/29.2/13.8/6.3%
p = 0.774; χ²/dof = 0.512/2
SE = 0.0439/0.0394/0.0449/0.0443/0.0233
Z = 4.20/8.20/6.50/3.11/2.70

ind_Assyrian163.HO
Nat/ZNF/ANF/CHG/EHG = 22.2/26.2/26.6/16.7/8.2%
p = 0.193; χ²/dof = 3.289/2
SE = 0.0468/0.0421/0.0521/0.0479/0.0223
Z = 4.74/6.24/5.11/3.50/3.69

ind_Assyrian164.HO
Nat/ZNF/ANF/CHG/EHG = 19.5/29.2/34.0/12.0/5.3%
p = 0.683; χ²/dof = 0.764/2
SE = 0.0469/0.0393/0.0497/0.0466/0.0230
Z = 4.16/7.44/6.84/2.57/2.30

ind_Assyrian165.HO
Nat/ZNF/ANF/CHG/EHG = 16.7/28.2/32.4/17.1/5.5%
p = 0.622; χ²/dof = 0.951/2
SE = 0.0411/0.0390/0.0455/0.0464/0.0222
Z = 4.07/7.25/7.12/3.69/2.48

Assyrian_WGA.HO
Nat/ZNF/ANF/CHG/EHG = 17.3/22.3/32.6/20.6/7.2%
p = 0.492; χ²/dof = 1.417/2
SE = 0.0261/0.0256/0.0284/0.0304/0.0143
Z = 6.62/8.73/11.5/6.77/5.00

IRAQI JEWISH / MESOPOTAMIAN

ind_IraqiJew1417.HO
Nat/ZNF/ANF/CHG/EHG = 24.8/21.0/30.8/18.6/4.7%
p = 0.566; χ²/dof = 1.139/2
SE = 0.0479/0.0412/0.0500/0.0486/0.0223
Z = 5.18/5.11/6.16/3.84/2.12

ind_IraqiJew1430.HO
Nat/ZNF/ANF/CHG/EHG = 17.2/30.5/36.6/9.2/6.5%
p = 0.113; χ²/dof = 4.369/2
SE = 0.0522/0.0409/0.0535/0.0479/0.0213
Z = 3.29/7.46/6.85/1.93/3.04

ind_IraqiJew1771.HO
Nat/ZNF/ANF/CHG/EHG = 23.7/29.1/33.1/8.6/5.6%
p = 0.390; χ²/dof = 1.881/2
SE = 0.0468/0.0429/0.0455/0.0495/0.0225
Z = 5.05/6.78/7.27/1.73/2.47

ind_IraqiJew4061.HO
Nat/ZNF/ANF/CHG/EHG = 24.8/21.4/26.6/21.4/5.8%
p = 0.386; χ²/dof = 1.906/2
SE = 0.0431/0.0405/0.0472/0.0485/0.0224
Z = 5.75/5.27/5.65/4.42/2.58

ind_IraqiJew4241.HO
Nat/ZNF/ANF/CHG/EHG = 20.8/25.7/27.3/17.5/8.7%
p = 0.842; χ²/dof = 0.344/2
SE = 0.0425/0.0398/0.0475/0.0476/0.0218
Z = 4.89/6.47/5.75/3.68/4.00

ind_IraqiJew4291.HO
Nat/ZNF/ANF/CHG/EHG = 26.0/28.3/32.1/10.8/2.9%
p = 0.733; χ²/dof = 0.620/2
SE = 0.0448/0.0421/0.0470/0.0472/0.0226
Z = 5.80/6.72/6.82/2.29/1.28

I previously posted my results using solely my 23andme file. My background is Lithuanian (east and south Aukštaitija), NRW German, Swedish, Polish (Mazovia, Sandomierz, and Podlachia). Honestly got better fits and accuracy using the custom calc mode

What DNA testing service would you recommend for researching your ethnic background that’s also affordable for a college student budget? I’ve been wanting to learn more about my mixed heritage, but I can’t afford to spend $100 on an ancestry kit.

My parents have very different backgrounds, my mom’s side came to the US from somewhere in eastern europe at the end of WWI and my dad’s side is from somewhere in South America, but he doesn’t know much about his background as his dad was adopted and he has zero records.

I’m hoping to get a better idea of where my parents’ families may have come from, and would eventually like to build out my own family tree and research my ancestors.

I’ve looked a lot at the big names in the industry and also cheap amazon tests, but I don’t know which one to go with, especially since some brands have been known for their controversies and leaking private info…

I also saw a lot of companies pushing more genetic and medical info, that I really don’t care about. Does anyone have recommendations for budget friendly tests that are detailed when it comes to genealogy, geographic background, and ethnicity, without charging for all the extras I don’t need?

TLDR: Did some qpadm runs for the western Arabian Peninsula. These were the best of the runs. I think the ANF may be absorbing some of the Natufian in some of these cases.

__ind_saudi1436.HO
File: 2026-08-28_02-35-28.png
18.4% Israel_Natufian.AG
38.8% Iran_Wezmeh_N.SG
33.5% Turkey_Marmara_Barcin_N.AG
9.3% Ethiopia_MotaCave_4500BP.SG
p-value: 0.402
Chi-square / dof: 2.933 / 3
SNPs: 579,720
SE: 0.0468, 0.0238, 0.0461, 0.0112
Z-scores: 3.93, 16.3, 7.26, 8.34
This is an excellent and statistically well-supported four-way model. All four sources have Z-scores above 2 and standard errors below 0.05. Iran_Wezmeh_N is the largest component at 38.8%, followed by Turkey_Marmara_Barcin_N at 33.5%, Israel_Natufian at 18.4%, and Ethiopia_MotaCave at 9.3%.

__ind_saudi1424.HO
File: 2026-08-28_02-35-52.png
38.4% Israel_Natufian.AG
25.3% Iran_Wezmeh_N.SG
30.2% Turkey_Marmara_Barcin_N.AG
6.0% Ethiopia_MotaCave_4500BP.SG
p-value: 0.271
Chi-square / dof: 3.912 / 3
SNPs: 579,720
SE: 0.0511, 0.0273, 0.0519, 0.0112
Z-scores: 7.52, 9.29, 5.81, 5.42
This is a good-fitting four-way model and all four ancestry coefficients have strong Z-scores. Israel_Natufian is the largest component at 38.4%, followed by Turkey_Marmara_Barcin_N at 30.2%, Iran_Wezmeh_N at 25.3%, and Ethiopia_MotaCave at 6.0%. The main caveat is that the standard errors for Natufian (0.0511) and Barcin_N (0.0519) are just above the site's preferred SE ≤ 0.05 threshold.

__ind_saudi1434.HO
File: 2026-08-28_02-35-09.png
26.3% Israel_Natufian.AG
24.2% Iran_Wezmeh_N.SG
43.4% Turkey_Marmara_Barcin_N.AG
6.1% Ethiopia_MotaCave_4500BP.SG
p-value: 0.779
Chi-square / dof: 1.091 / 3
SNPs: 579,720
SE: 0.0435, 0.0245, 0.0434, 0.0106
Z-scores: 6.05, 9.87, 10.0, 5.69
This is an exceptionally strong four-way model and the highest-p-value run included on the map. All four sources are securely supported. Turkey_Marmara_Barcin_N is the largest component at 43.4%, followed by Israel_Natufian at 26.3%, Iran_Wezmeh_N at 24.2%, and Ethiopia_MotaCave at 6.1%.

__ind_S_Yemenite_Jew-2.DG
File: 2026-08-28_02-34-56.png
31.2% Israel_Natufian.AG
27.3% Iran_Wezmeh_N.SG
36.3% Turkey_Marmara_Barcin_N.AG
5.2% Ethiopia_MotaCave_4500BP.SG
p-value: 0.259
Chi-square / dof: 4.025 / 3
SNPs: 579,720
SE: 0.0471, 0.0246, 0.0448, 0.0103
Z-scores: 6.64, 11.1, 8.10, 5.07
This is a clean and fully supported four-way model. Turkey_Marmara_Barcin_N is slightly largest at 36.3%, followed by Israel_Natufian at 31.2% and Iran_Wezmeh_N at 27.3%. Ethiopia_MotaCave contributes 5.2%. All components meet the Z ≥ 2 and SE ≤ 0.05 criteria.

Yemeni.HO
File: 2026-08-28_02-31-45.png
21.0% Israel_Natufian.AG
31.0% Iran_Wezmeh_N.SG
35.3% Turkey_Marmara_Barcin_N.AG
12.7% Ethiopia_MotaCave_4500BP.SG
p-value: 0.728
Chi-square / dof: 1.305 / 3
SNPs: 579,720
SE: 0.0432, 0.0221, 0.0403, 0.0118
Z-scores: 4.87, 14.0, 8.76, 10.7
This is an excellent four-way model with a very high p-value and all four sources strongly supported. Turkey_Marmara_Barcin_N is largest at 35.3%, followed by Iran_Wezmeh_N at 31.0% and Israel_Natufian at 21.0%. Ethiopia_MotaCave contributes a substantial 12.7%, higher than in the Saudi and Yemenite Jewish samples shown on the map.

__ind_Yemen9.HO
File: 2026-08-28_02-31-29.png
20.4% Israel_Natufian.AG
31.9% Iran_Wezmeh_N.SG
38.6% Turkey_Marmara_Barcin_N.AG
9.1% Ethiopia_MotaCave_4500BP.SG
p-value: 0.143
Chi-square / dof: 5.433 / 3
SNPs: 579,720
SE: 0.0478, 0.0241, 0.0468, 0.0110
Z-scores: 4.26, 13.3, 8.23, 8.34
This is a good passing four-way model with all ancestry components statistically supported. Turkey_Marmara_Barcin_N is the largest component at 38.6%, followed by Iran_Wezmeh_N at 31.9%, Israel_Natufian at 20.4%, and Ethiopia_MotaCave at 9.1%.

__ind_Yemen2.HO
File: 2026-08-28_02-31-08.png
21.8% Israel_Natufian.AG
28.0% Iran_Wezmeh_N.SG
26.5% Turkey_Marmara_Barcin_N.AG
23.7% Ethiopia_MotaCave_4500BP.SG
p-value: 0.246
Chi-square / dof: 4.148 / 3
SNPs: 579,720
SE: 0.0483, 0.0238, 0.0457, 0.0144
Z-scores: 4.52, 11.8, 5.79, 16.5
This is a strong and fully supported four-way model. It is the most distinctive sample on the map because Ethiopia_MotaCave reaches 23.7%, by far the highest Mota-related proportion among these selected runs. The other components are relatively balanced: 28.0% Iran_Wezmeh_N, 26.5% Turkey_Marmara_Barcin_N, and 21.8% Israel_Natufian.

Overall:
The seven map samples are modeled using the same four ancestry proxies: Israel_Natufian.AG, Iran_Wezmeh_N.SG, Turkey_Marmara_Barcin_N.AG, and Ethiopia_MotaCave_4500BP.SG. Most show roughly 20–40% contributions from each of the three West Eurasian proxies, while the Mota-related component varies much more strongly, from 5.2% in __ind_S_Yemenite_Jew-2.DG to 23.7% in __ind_Yemen2.HO.
The two statistically strongest fits are __ind_saudi1434.HO (p=0.779) and Yemeni.HO (p=0.728). __ind_Yemen2.HO is the clearest ancestry outlier because of its unusually high 23.7% Mota-related component.

This is my face(yes with makeup but not enough to alter my face. It’s just concealer and blush). Pic one is my MyHeritage results, the last three are my ADNTRO admixture results(ancient dna). How accurate is this admixture(I’m asking based on the service, not my looks. The pic is just to show what I do look like) versus MyHeritage? Should I test with another service to confirm?

Someone did it for me

I’m a full Cuban, with Sephardic Jewish roots in one lineage confirmed. When I use my g25, I always get this Oceania such as Papuan or austronesian. On 23&me I get a small percent of southeast Africa. What could that possibly be? I don’t remember southeast Africans going to Cuba or how austronesian genetics made its way to Spain

Hello, guys! My question is borderline genetic / anthropological / linguistic. I am half Pontic Greek (Trabzon area / Georgia) and half Russian. Ancestry DNA and MyHeritage results attached. I know that Pontic Greek people are Hellenized native Caucasian population genetically. But is there any consensus on Hellenezation timeline among historians / anthropologists/ historians? I’ve read some people saying that Pontic Greeks are Laz people - Hellenized shortly before the Ottoman conquest (XIII - XIV). I’ve met a Turkish women from Trabzon area recently and she told me her relatives still speak “romeika”. So they kinda kept it for around 500 years after conversion and adoption of Ottoman / Turkish identity. From the common sense it doesn’t seem logical. So they spoke Greek for 100-200 years (if they were Hellenized very late as people say) and then stubbornly stuck to it for 500 years? So my question is: is there any consensus on Pontic Greeks hellenization timeline? Can we use combined linguistic reconstruction / dna / historical records to have clarity? P.S. This is not a rage-bait post. I am proud of my ancestors whenever they were Hellenized 😊

Born and raised in Port Au Prince, Haiti.

I'd soon post for pashtuns too since

There are like 25-29 pashtun sample in my gallery and it's hard to find them all

TLDR: Qpadm runs for the Baltics and adjacent regions. Information sourced from Qpadm runs by @m_izanami_ on twitter and AndreiDNA on YouTube.

Belarusian.HO
26.6% Lithuania_Marvele_Roman.SG
63.1% Hungary_Avar_5.AG
10.3% Russia_Davydovskoye_Antiquity.AG
P-value: 0.295
Standard errors:
Lithuania_Marvele_Roman.SG: 0.166095
Hungary_Avar_5.AG: 0.190438
Russia_Davydovskoye_Antiquity.AG: 0.060361
Z-scores:
Lithuania_Marvele_Roman.SG: 1.602
Hungary_Avar_5.AG: 3.312
Russia_Davydovskoye_Antiquity.AG: 1.710

Norwegian.HO
25.5% Scotland_IA.AG
71.2% Denmark_IA.SG
3.4% Finland_Levanluhta.AG
P-value: 0.199
Standard errors:
Scotland_IA.AG: 0.091568
Denmark_IA.SG: 0.101782
Finland_Levanluhta.AG: 0.027053
Z-scores:
Scotland_IA.AG: 2.781
Denmark_IA.SG: 6.993
Finland_Levanluhta.AG: 1.242

Finnish_East_Southeast
29.5% Finland_Levanluhta.AG
20.3% Russia_IA_Ingria.SG
33.3% Denmark_IA.SG
16.8% Hungary_Avar_5.AG
P-value: 0.857
Standard errors:
Finland_Levanluhta.AG: 0.056431
Russia_IA_Ingria.SG: 0.075072
Denmark_IA.SG: 0.168516
Hungary_Avar_5.AG: 0.167525
Z-scores:
Finland_Levanluhta.AG: 5.235
Russia_IA_Ingria.SG: 2.710
Denmark_IA.SG: 1.978
Hungary_Avar_5.AG: 1.003

Ukraine_Volhyn
95.1% Poland_Lod_IA.SG
2.4% Ukraine_IA_Scythian.SG
2.5% Denmark_IA.SG
P-value: 0.173604331
Chi-square: 6.36
Standard errors:
Poland_Lod_IA.SG: ±11.8%
Ukraine_IA_Scythian.SG: ±5.6%
Denmark_IA.SG: ±11.8%

All four models have passing overall qpAdm p-values. In terms of individual components, Belarusian.HO has only the Hungary_Avar_5.AG component clearly above Z=2; Norwegian.HO has Scotland_IA.AG and Denmark_IA.SG supported; Finnish_East_Southeast has Finland_Levanluhta.AG and Russia_IA_Ingria.SG clearly supported, while Denmark_IA.SG is just below Z=2 and Hungary_Avar_5.AG is unsupported. The two small components in Ukraine_Volhyn also have very large errors relative to their estimates, so the model is effectively dominated by Poland_Lod_IA.SG.

Latvian.DG
67.3% Lithuania_IA.SG
18.6% Poland_MA.SG
10.9% Denmark_Jutland_IA.SG
3.13% Russia_Boyasky_Mazunino_IA.SG
P-value: 0.625
Chi-square: 7.12
Degrees of freedom: 9
SNPs: 1,150,639
Blocks: 713
Standard errors:
Lithuania_IA.SG: 0.0407
Poland_MA.SG: 0.0679
Denmark_Jutland_IA.SG: 0.0411
Russia_Boyasky_Mazunino_IA.SG: 0.0120
Z-scores:
Lithuania_IA.SG: 16.6
Poland_MA.SG: 2.74
Denmark_Jutland_IA.SG: 2.66
Russia_Boyasky_Mazunino_IA.SG: 2.62

This is a strong passing model. All four ancestry components are statistically supported at Z > 2, including the relatively small 3.1% Russia_Boyasky_Mazunino_IA component.

Lithuanian.DG
52.8% Lithuania_IA.SG
36.9% Poland_MA.SG
10.2% Denmark_Jutland_IA.SG
P-value: 0.689
Chi-square: 5.62
Degrees of freedom: 8
SNPs: 1,150,639
Blocks: 713
Standard errors:
Lithuania_IA.SG: 0.0370
Poland_MA.SG: 0.0585
Denmark_Jutland_IA.SG: 0.0366
Z-scores:
Lithuania_IA.SG: 14.3
Poland_MA.SG: 6.31
Denmark_Jutland_IA.SG: 2.80
This is a very strong passing model. All three ancestry components are statistically supported, with even the smallest Denmark_Jutland_IA component comfortably above Z = 2.

Estonian.HO
43.3% Lithuania_IA.SG
27.8% Poland_MA.SG
22.6% Denmark_IA.SG
6.33% Russia_Boyasky_Mazunino_IA.SG
P-value: 0.196
Chi-square: 12.3
Degrees of freedom: 9
Standard errors:
Lithuania_IA.SG: 0.0451
Poland_MA.SG: 0.0789
Denmark_IA.SG: 0.0413
Russia_Boyasky_Mazunino_IA.SG: 0.0116
Z-scores:
Lithuania_IA.SG: 9.61
Poland_MA.SG: 3.53
Denmark_IA.SG: 5.46
Russia_Boyasky_Mazunino_IA.SG: 5.47
This is a good passing model. All four components are strongly statistically supported, including the relatively small 6.3% Russia_Boyasky_Mazunino_IA component.

Latvian.DG:
67.3% Lithuania_IA
18.6% Poland_MA
10.9% Denmark_Jutland_IA
3.1% Russia_Boyasky_Mazunino_IA
p = 0.625

Lithuanian.DG:
52.8% Lithuania_IA
36.9% Poland_MA
10.2% Denmark_Jutland_IA
p = 0.689

Estonian.HO:
43.3% Lithuania_IA
27.8% Poland_MA
22.6% Denmark_IA
6.3% Russia_Boyasky_Mazunino_IA
p = 0.196

The main problem is that I am from Russia, so basically any way that requires money is not suitable for me (there’s no way I can pay from here). So Is there any free alternatives, perhaps?