Mega QAPDM Models thread

I'm going to be experimenting with this combination more and see if I can get these standard errors down:

Attachment 144177

https://i.postimg.cc/43Ky3cXK/kddjsfjsfjsjf.png

About the best I can do with this combination

Attachment 144257

Tried VK579 instead

Attachment 144258

Both were ran with the Gernarchivist references I think Opie linked in an earlier post.

Attachment 144259

Quote:

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Originally Posted by Lard

PCA vs. qpAdm: More Similar Than People Think

Fundamentally, autosomal PCA and qpAdm modeling operate on the same basic idea:
They both assess how populations are related based on genome-wide allele frequencies — just using different statistical approaches.

• PCA uses principal components to reduce genetic variance into 2D/3D plots, revealing clustering patterns.
• qpAdm estimates ancestry proportions by modeling a test population as a mix of chosen “left” sources, with “right” reference groups to anchor the model.

But in both cases, your results depend almost entirely on your inputs.
You can cherry-pick populations in either method — and get misleading results that still “look” scientific.

Why qpAdm Isn't Immune to Narrative Bias

There’s a tendency to treat qpAdm as more rigorous than PCA, and while it can be more formalized, it’s just as vulnerable to biased modeling choices.

That’s why so many published studies claim Ashkenazi Jews are “50%+ Levantine” — even though PCA consistently places them overlapping with Southern Italians.

Here’s why:
Most of these studies use deeply flawed European proxies — Northern Italians, French, Sardinians, or even Tuscans — while completely ignoring Southern Italians or Sicilians. This artificially inflates the Levantine component, because these proxies are genetically too distant and don't match PCA placement.

The qpAdm model still returns a “feasible” result — because qpAdm doesn't know your sources are bad.
It just fits whatever you give it.

In other words: Bad source selection in qpAdm doesn’t get corrected by the math — it gets rewarded. The tool will give you a p-value and ancestry breakdown that looks clean, but is fundamentally built on cherry-picked assumptions.

PCA-Informed qpAdm is the Solution

That’s why my models start with PCA — which clearly shows Ashkenazi Jews clustering directly on top of Southern Italians — and then use qpAdm to test models that reflect that structure.

Examples from my thread:
Stable qpAdm Models of Ashkenazi Jewish Ancestry – Ignoring PCA No More

Models such as:

• Italian_South.HO + Lebanese_Muslim.HO
• Italian_South.HO + Israel_Ashkelon_LBA.AG
• Italian_South.HO + Israel_C_o2.AG

All produce stable 2-way models with:

• ~75–78% Southern Italian–like ancestry
• ~22–25% Levantine
• Strong p-values and standard errors
• Full consistency with PCA and historical records

This matches not just the genetic structure, but also the well-documented Roman and Byzantine-era Jewish presence in Southern Italy.

Visual Results

https://i.ibb.co/M0ZfVqC/1.png
Modern Levantine Proxy model

https://i.ibb.co/S4FnRm4s/2.png
Bronze Age Coastal Levantine (Philistine-admixed)

https://i.ibb.co/G43Kn5wk/3.png
Inland Bronze Age Levantine (likely Israelite/Canaanite)

Don’t Let Narrative Modeling Skew the Data

You can go check nearly any study by Behar, Hammer, or Ostrer — they almost all use Northern Italians or French as the European side of the model.
Even YouTubers like Andrei DNA — who is also an Apricity forum member — repeat the same setup and get the same distorted results: Ashkenazi Jews as a “Middle Eastern” population.

But if Ashkenazi Jews sit right on top of Southern Italians in PCA — and they do — then they’re no more “Middle Eastern” than a Calabrian is.

That’s why PCA-aligned qpAdm is essential — and narrative-driven modeling needs to be called out.
https://www.youtube.com/watch?v=5gxr79HfpYQ

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You need southern Italians, Levantines, and Northern Europeans to model Ashkenazi Jews.

Using AndreiDNA's right and left populations, I modeled my Basal Eurasian admixture.


https://www.youtube.com/watch?v=t59yXBo1MoI





Attachment 144721
Attachment 144724


Mbuti is the proxy for Basal Eurasian.

Quote:

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Originally Posted by Gannicus

Mbuti is the proxy for Basal Eurasian.

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Bad proxy in my opinion.

Target: Israel_Natufian
Distance: 27.4820% / 0.27482024
97.4 Russia_Kostenki14
2.6 Mbuti

Target: Georgia_Kotias.SG
Distance: 28.6263% / 0.28626346
100.0 Russia_Kostenki14

Target: Iran_GanjDareh_N
Distance: 27.1517% / 0.27151689
99.8 Russia_Kostenki14
0.2 Mbuti

Quote:

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Originally Posted by userNa

Bad proxy in my opinion.

Target: Israel_Natufian
Distance: 27.4820% / 0.27482024
97.4 Russia_Kostenki14
2.6 Mbuti

Target: Georgia_Kotias.SG
Distance: 28.6263% / 0.28626346
100.0 Russia_Kostenki14

Target: Iran_GanjDareh_N
Distance: 27.1517% / 0.27151689
99.8 Russia_Kostenki14
0.2 Mbuti

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You can't use G25 like that. It has to do with the outgroups that Andrei selected in his video. He made that video on it 4 months ago. Perhaps he has changed his mind on the method. It'd be nice if he could comment on it.

Quote:

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Originally Posted by Gannicus

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I've seen his videos.

In my opinion what shows up as Mbuti in his model is just an out-of-africa wave that postdates the first Eurasian arrivals and not actual African admixture.

Quote:

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Originally Posted by userNa

I've seen his videos.

In my opinion what shows up as Mbuti in his model is just an out-of-africa wave that postdates the first Eurasian arrivals and not actual African admixture.

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Right, it's not African at all. It's his attempt to measure Basal Eurasian that's using Mbuti as a proxy. Using his model with his source populations and reference populations it's speculated that I have 24% basal eurasian admixture. I thought it was interesting. So, I decided to share it.

Anyways back to the more typical modeling. Using Xaviers references a few posts ago I modeled myself with 2 Iron age sources, Norway IA and Czechia IA Hallstatt.

Attachment 144728


Target: Gannicus_MergedFile_officialDavidski_scaled
Distance: 0.0326% / 0.03258002
66.6 Czech_IA_Hallstatt
33.4 Norway_IA.SG

Attachment 144729


Target: Gannicus_MergedFile_officialDavidski_scaled
Distance: 0.0326% / 0.03258002
66.6 Czech_IA_Hallstatt
33.4 Norway_IA.SG