Balto-Slavic scale

[Token]

Hungarians are a Nordo-Slavic mix like northeast Germans? this doesn't make sense.

could you try it with these outgroups?

set 1: Anatolia_N (25), CHG (2), EHG (4), ElMiron (1), Iran_Ganj_Dareh_N (3),
Jordan_PPNB (1), MA1 (1), Mbuti (10), Natufian (6), Ust_Ishim (1), Vestonice16 (1), WHG (6),
Russia_Yamnaya_Samara (9)

set 2: Anatolia_N (25), CHG (2), EHG (4), ElMiron (1), GoyetQ116-1 (1), Iran_Ganj_Dareh_N (3),
Jordan_PPNB (1), Kostenki14 (1), MA1 (1), Morocco_Iberomaurusian (6), Mota (1), Natufian (6),
Ust_Ishim (1), Vestonice16 (1), Italy_Villabruna (1), WHG (6), Russia_Yamnaya_Samara (9).

that's what was used in the Rome study

I will when i get home, but i can tell you in advance that they will show the same thing ('ve tried similar setups).

[Aren]

No, my right pops are very solid for my purpose, have you bothered reading Patterson's notes or looking at the supp. files of genetic papers? Actually i am being quite restrictive here.

Your observations are all based on Global25 so they are meaningless for formal stats, run your qpAdm model and prove me wrong (spoiler: they will show the same). There is no East Eurasian in this Hungarian sample, albeit i am pretty sure Hungarians from the Great Plain will show some.

My observation is sollely based on what someone else who is very much an expert of qpAdm who I've talked to regarding these things. I personally don't use it.
qpAdm is easily manipulated and gives different results if one isn't careful with the right pops from what I've heard. You right pops seem indeed very restrictive for the run you're making. Probably needs more recent samples.
Like I said I don't use qpAdm but every study I've viewed which used qpAdm to modell modern populations clearly shows higher Barcin related admixture for Hungarians than either Scandinavians or Northern Slavs(such as Haak et al just on top of my mind).

I'm not willing to discuss this though, to me it's very much a no brainer that Hungarians and other central Europeans have non-Germanic and non-Slavic input which shifts them south, whether is Celtic, Paleo-Balkan or Greco-Roman.

[Token]

...
Like I said I don't use qpAdm but every study I've viewed which ...

Sure you don't.

[Freeroostah]

Target: VangosH_scaled
Distance: 2.0434% / 0.02043351
55.0 Greco-Roman
21.8 Balkan
12.2 Slavic
11.0 Baltic


Balto-Slavic is equally distributed

[Jana]

Target: VangosH_scaled
Distance: 2.0434% / 0.02043351
55.0 Greco-Roman
21.8 Balkan
12.2 Slavic
11.0 Baltic


Balto-Slavic is equally distributed

Calculator is designed to run at 0.25X, not 0 pen.

[Ljubic]

Target: Greatuncle_scaled
Distance: 3.1536% / 0.03153571 | ADC: 0.25x
60.8 Slavic
34.0 Balkan
3.4 Greco-Roman
1.8 Baltic

Target: Father_scaled
Distance: 2.7417% / 0.02741686 | ADC: 0.25x
60.2 Slavic
21.8 Balkan
14.4 Greco-Roman
3.6 Baltic

Target: Ljubic_scaled
Distance: 1.9318% / 0.01931850 | ADC: 0.25x
67.2 Slavic
26.4 Balkan
6.4 Greco-Roman

Edit: Should have read the post above

[Token]

I've been playing with this Hungarian academic average with qpAdm. Apparently they don't need anything besides Germanic and Slavic, the Balkan stuff is just Global25 overfitting the data. This is one of the models that i ran (obs: qpAdm does not distinguish North Europeans, so Germany_EMedieval is a stand in for both Slavic and Germanic. The exact proportions of both should be analysed using G25):

Hungarian
Germany_EMedieval 0.873 +- 0.100
Lech_MBA 0.127 +- 0.100
chisq 10.154
tail prob 0 516617

So Lech_MBA isn't required (and neither are Hungary_Scythian and Croatia_EIA) since the std.error is basically equal to the admixture coefficient, so the nested model with only Germany_EMedieval (p-value: 0.14) is closer to optimal.

Full output:

left pops:
Hungarian
Germany_EMedieval.SG
Germany_Lech_MBA

right pops:
Czech_Vestonice16
Russia_Ust_Ishim.DG
Russia_MA1_HG.SG
Italy_North_Villabruna_HG
Jordan_PPNB
Romania_Mesolithic_IronGates
Georgia_Satsurblia.SG
Morocco_Iberomaurusian
Iran_GanjDareh_N
Cameroon_SMA.DG
Anatolia_N
Russia_Steppe_Eneolithic
Russia_HG_Karelia

  0            Hungarian   20
  1 Germany_EMedieval.SG   35
  2     Germany_Lech_MBA    7
  3    Czech_Vestonice16    1
  4  Russia_Ust_Ishim.DG    1
  5     Russia_MA1_HG.SG    1
  6 Italy_North_Villabruna_HG    1
  7          Jordan_PPNB    4
  8 Romania_Mesolithic_IronGates    4
  9 Georgia_Satsurblia.SG    1
 10 Morocco_Iberomaurusian    6
 11     Iran_GanjDareh_N    8
 12      Cameroon_SMA.DG    1
 13           Anatolia_N   22
 14 Russia_Steppe_Eneolithic    3
 15    Russia_HG_Karelia    2
jackknife block size:     0.050
snps: 593124  indivs: 117
number of blocks for block jackknife: 711
dof (jackknife):   602.170
numsnps used: 46474
codimension 1
f4info: 
f4rank: 1 dof:     11 chisq:    10.154 tail:           0.51661742 dofdiff:     13 chisqdiff:   -10.154 taildiff:                    1
B:
          scale     1.000 
Russia_Ust_Ishim.DG     1.491 
Russia_MA1_HG.SG     1.268 
Italy_North_Villabruna_HG     0.060 
    Jordan_PPNB    -0.175 
Romania_Mesolithic_IronGates     1.095 
Georgia_Satsurblia.SG     0.757 
Morocco_Iberomaurusian     0.364 
Iran_GanjDareh_N     0.759 
Cameroon_SMA.DG     1.266 
     Anatolia_N     0.177 
Russia_Steppe_Eneolithic     1.180 
Russia_HG_Karelia     1.621 
A:
          scale   941.312 
Germany_EMedieval.SG     0.204 
Germany_Lech_MBA    -1.399 


full rank 1
f4info: 
f4rank: 2 dof:      0 chisq:     0.000 tail:                    1 dofdiff:     11 chisqdiff:    10.154 taildiff:           0.51661742
B:
          scale     1.000     1.000 
Russia_Ust_Ishim.DG     1.520    -0.475 
Russia_MA1_HG.SG     1.145     0.221 
Italy_North_Villabruna_HG     0.102     0.032 
    Jordan_PPNB    -0.226     1.608 
Romania_Mesolithic_IronGates     1.080     0.028 
Georgia_Satsurblia.SG     0.674     1.886 
Morocco_Iberomaurusian     0.357     1.491 
Iran_GanjDareh_N     0.776     0.505 
Cameroon_SMA.DG     1.309    -0.603 
     Anatolia_N     0.145     1.543 
Russia_Steppe_Eneolithic     1.170     0.137 
Russia_HG_Karelia     1.692    -0.584 
A:
          scale   991.102  3066.804 
Germany_EMedieval.SG     0.674     1.243 
Germany_Lech_MBA    -1.243     0.674 


best coefficients:     0.873     0.127 
ssres:
    0.000479023     0.000581661     0.000056186     0.000515624     0.000479649     0.001012712     0.000723984     0.000529943     0.000338111     0.000651928     0.000560565     0.000512255 
    0.828304055     1.005779384     0.097153245     0.891591578     0.829385221     1.751132727     1.251877553     0.916352117     0.584644749     1.127281671     0.969301143     0.885767176 

Jackknife mean:      0.864886518     0.135113482 
      std. errors:     0.100     0.100 

error covariance (* 1000000)
     10007     -10007 
    -10007      10007 


    fixed pat  wt  dof     chisq       tail prob
           00  0    11    10.154        0.516617     0.873     0.127 
           01  1    12    12.339        0.418882     1.000    -0.000 
           10  1    12    41.981     3.35445e-05     0.000     1.000 
best pat:           00         0.516617              -  -
best pat:           01         0.418882  chi(nested):     2.185 p-value for nested model:        0.139368

Update: after rotating outgroups many times i was able to flesh out some Balkan admixture in present-day Hungarians. I obtained 0.77 North European + 0.23 Lech_MBA, std error 0.1. That is almost identical to the results obtained with G25, which certainly strenghtens the hypothesis, even though you could call the analysis 'biased'.

[oszkar07]

Target: Oszkar Hungarian/British
Distance: 1.9092% / 0.01909200 | ADC: 0.5x RC
42.8 Germanic
27.2 Slavic
17.8 Balkan
12.2 Celtic

[MandM]

Almost identical, so close hehe

Target: Serbian
Distance: 1.1471% / 0.01147061 | ADC: 0.25x

51.0 Slavic
37.6 Balkan
11.4 Greco-Roman

Target: Milenko_scaled
Distance: 1.8421% / 0.01842136 | ADC: 0.25x RC
50.4 Slavic
38.6 Balkan
11.0 Greco-Roman

[Scandal]

WEST SLAVS

Target: Polish
Distance: 1.0294% / 0.01029432 | ADC: 0.25x

86.0 Slavic
9.6 Germanic
4.4 Baltic

Target: Slovakian
Distance: 1.9145% / 0.01914454 | ADC: 0.25x

84.2 Slavic
10.8 Balkan
4.2 Germanic
0.8 Baltic

Target: Sorb_Niederlausitz
Distance: 1.9298% / 0.01929826 | ADC: 0.25x

67.0 Slavic
18.2 Baltic
14.8 Balkan

Target: Czech
Distance: 1.1885% / 0.01188460 | ADC: 0.25x

56.6 Slavic
34.2 Germanic
5.2 Balkan
2.6 Greco-Roman
1.4 Celtic

I am surprised Sorbs score zero germanic. I guess the ones who did mix with the germans assimilated into the ethnic german population.