
Turkish DNA: Ancient Origins from Neolithic Anatolia to the Ottomans
Turkish ancestry through ancient DNA: the Anatolian farmer substrate, the Southern Arc results, Byzantine Anatolia, the modest Turkic layer and qpAdm.
Articles
97 articles on qpadm, ancient-DNA research written up for readers who want the evidence, not just the headline.
qpAdm is the formal admixture method of the ancient-DNA literature — it models one target population as a weighted mixture of chosen sources, measured against a set of outgroups, and unlike every percentage calculator it can reject a model outright. That property is why published papers lean on it, and why reading one takes more than reading percentages.
The articles here cover the method end to end: a structured learning path from the f4-statistics underneath to running models in R, the current best-practices checklist with the measured numbers behind every rule, the practical pipeline from a raw file to an AADR merge, the parameters that silently change results, population-specific model recipes for European, South Asian and Middle Eastern ancestry, the companion methods (qpGraph, f4-ratios, admixture dating), and worked examples from reports run against AADR v66.
What the paid qpAdm analysis includes
Turkish ancestry through ancient DNA: the Anatolian farmer substrate, the Southern Arc results, Byzantine Anatolia, the modest Turkic layer and qpAdm.

Amazigh and Maghrebi ancestry through ancient DNA: Taforalt, the Neolithic farmers, the Guanche genomes, Arab-era gene flow, the Saharan gradient and qpAdm.

Somali ancestry through ancient DNA: the East African Pastoral Neolithic, the Ethio-Somali component, Arabian contacts and how to model it with qpAdm.

Punjabi ancestry through ancient DNA: the Indus Periphery and Rakhigarhi genomes, AASI, the Steppe MLBA layer, the Swat Iron Age references and qpAdm.

What ancient genomes say about Pashtun ancestry: Iranian farmer, AASI and Steppe streams, the Swat valley references, and the legends DNA cannot confirm.

What genomes say about Bengali ancestry: a strong AASI share, a Southeast Asian layer from Austroasiatic and Tibeto-Burman speakers, and the gaps in the data.

What genomes say about Mexican and Latino ancestry: the peopling of the Americas, Indigenous Mexican structure, post-1519 admixture and diaspora variation.

What genomes say about African American ancestry: West and West Central African source regions, the European share and its sex bias, and the ancient DNA gap.

A structured learning path through everything qpAdm — what to read in what order, from the f4-statistics underneath to running models in R, choosing outgroups, reading results and knowing the method's measured limits.

The definitive working checklist for qpAdm in 2026 — temporal stratification, right-set construction, lowest-rank-first search, composite feasibility and reporting standards — each rule carrying its measured justification from the 2021–2025 audit literature.

qpAdm has been audited harder than any tool in ancient DNA: measured false-discovery rates, resolution floors, protocol failures. What the 2021–2025 criticism literature actually established, what survived it, and how practice changed.

The Middle East is where qpAdm's sources crowd closest together: Natufian, Anatolian, Iranian and Caucasus ancestries all interrelated. The working recipe, the right set that splits them, failure modes and a worked reading.

South Asia is qpAdm's hardest standard fixture: one ancestral stream has no ancient sample at all. The working recipe — Indus Periphery, steppe MLBA, the Onge-as-AASI-proxy problem — with right sets, failure modes and a worked reading.

The three-source model that rebuilt European prehistory — WHG, Anatolian farmers, steppe pastoralists — as a working qpAdm recipe: exact source and right-set choices, regional adjustments, failure modes and a worked reading.

qpAdm says how much; linkage-disequilibrium decay says when. How DATES and ALDER read generation counts out of chromosome fragment lengths, what the dates mean, and how a date corroborates or breaks a qpAdm model.

Before qpAdm there was the f4-ratio — one number, two f4-statistics, an ancestry proportion. How the classic estimator works, the famous results built on it, and the precise trade against qpAdm.

qpAdm's bigger sibling models whole population histories as trees with admixture edges. How qpGraph works, what find_graphs automates, and the 2023 finding that reshaped how graph results should be read.

Same model, different p-value: the real differences between original qpAdm and ADMIXTOOLS 2 — allsnps semantics, fudge_twice, f2 precomputation — and the settings that reproduce classic behaviour when you need to.

The suffixes on AADR population labels encode how each genome was produced — capture, shotgun, diploid, array — and mixing them carelessly biases f-statistics. What each label means and the selection rules that keep models honest.

The settings tutorials skip and reviewers ask about: extract_f2 versus genotype input, allsnps, maxmiss, fudge and fudge_twice, blgsize, boot, afprod and constrained — what each does, with the measured stakes.

The undocumented half of every qpAdm analysis: file formats, genome builds, strand hygiene, convertf and Poseidon, and the merge arithmetic that decides your standard errors before any model runs.

England has ancient DNA's best-measured migrations: a Beaker-era turnover, a mid-Bronze Age Celtic-era influx, the quantified Anglo-Saxon settlement and the Danelaw. What each layer left in English genomes, and how to read yours.

Egypt finally has ancient genomes: what the Old Kingdom and mummy-era samples show about ancient Egyptian ancestry, how the modern Nile gene pool differs, and how to read an Egyptian genome honestly.

Ancient DNA on the western Balkans: the Illyrian-era base, the measured Slavic-era arrival, why the world's highest I2a frequencies sit in Bosnia — and why the three nations' genomes overlap almost completely.

Ancient DNA on Bulgarian ancestry: the Thracian-era Balkan base, the Roman provincial centuries, the measured Slavic-era layer, the surprisingly thin Bulgar trace — and how to read a Bulgarian genome.

What ancient DNA says about Romanian ancestry: the Balkan deep stack, Dacians and the Roman province, the measured Slavic-era layer, highland continuity — and what the data cannot settle about the ethnogenesis debate.

Ancient DNA solved Hungary's founding paradox: the conquerors' genomes have been sequenced, and modern Hungarians barely carry them. The Carpathian Basin's layered story, and how to read a Hungarian genome.

Ukraine holds the Yamnaya homeland, the Trypillia mega-sites and the likeliest cradle of the Slavic expansion. What ancient DNA shows about Ukrainian ancestry, and how to read a Ukrainian genome.

Russian ancestry is a Slavic core laid over older northern and steppe worlds: what ancient DNA shows about the East Slavic expansion, the Uralic-related north, the steppe south, and how to read a Russian genome.

France's ancient-DNA transect runs from Ice Age refuges through Gaulish continuity to a nation of regional clines. What the samples show about French ancestry, why the Franks barely register, and how to read a French genome.

Denmark, Sweden and Norway share a genome written by two prehistoric turnovers and one famous exchange: the Viking Age imported as much ancestry as it exported. The ancient-DNA story, and how to read a Scandinavian genome.

What ancient DNA says about Scottish ancestry: the shared Beaker-descended base, the Pictish genomes and their local roots, the Gaelic-Irish kinship of the west, and the measured Norse layer in the isles.

The Netherlands sits at the heart of the Beaker world and the launch coast of the Anglo-Saxon migration. What ancient DNA shows about Dutch ancestry, the country's surprising internal cline, and how to read a Dutch genome.

Looking for an IllustrativeDNA alternative? The real decision points — coordinate reports versus hand-checked qpAdm, subscription versus one-time, WGS input, published statistics — and which services deliver each.

Rome's ancient-DNA transect, the Iron Age base, the imperial eastern shift, why Italy holds Europe's largest internal genetic variation, and what Sardinia preserves. How to read an Italian genome, region by region.

What ancient DNA says about Greek ancestry: the Aegean's Neolithic base, Minoan and Mycenaean genomes, the classical and Byzantine continuum, the Slavic-era addition, and the measured continuity underneath. How to read a Greek genome.

Sicily's ancient-DNA record runs from island foragers through a late steppe arrival, Greek and Phoenician colonists, Roman, Arab and Norman centuries. What each layer actually left in Sicilian genomes, and how to read your own.

Iberia has the longest continuous ancient-DNA transect in Europe: foragers, farmers, a Beaker-era Y-chromosome revolution, Phoenicians and Romans, the Islamic centuries and their aftermath. What each layer left, and how to read an Iberian genome.

Ireland's ancient-DNA transect is one of Europe's cleanest: a Mesolithic baseline, a Neolithic of tomb-builders with a dynastic elite, a near-total Beaker-era turnover, and striking continuity since. The story, and how to read an Irish genome.

Germany is ancient DNA's best-sampled territory: the LBK farmers, the Corded Ware steppe arrival, Bell Beakers, and the Celtic–Germanic–Slavic interfaces all run through it. The layered story, and how to read a German genome.

Poland's ancient-DNA story has a twist most national histories lack: a documented population turnover in the first millennium CE. Goths and Wielbark, the early Slavic horizon, what modern Polish genomes show, and how to read your own.

Iran holds one of ancient DNA's founding populations. What the Zagros genomes changed, how the plateau's ancestry formed and persisted through empires, what modern Iranian samples show, and how to read your own results.

Ancient DNA gives Armenians one of West Asia's clearest stories: a Bronze Age blend of local Caucasus and Anatolian streams, a measured steppe pulse, and genetic isolation since roughly the end of the Bronze Age. The evidence, honestly read.

Georgia holds two of the most important genomes in West Eurasian prehistory. What Satsurblia and Kotias revealed, the Kura-Araxes and later layers, why Georgian ancestry is among Eurasia's most continuous, and how to read your own results.

Kurdish ancestry through the ancient-DNA lens: the Zagros Neolithic foundation, the layers that followed, what modern samples show about structure and neighbours, and how to read G25 and qpAdm results for a Kurdish genome.

What ancient DNA and modern genetic studies say about Assyrian ancestry: deep Mesopotamian roots, two millennia of documented endogamy, the missing ancient transect, and how to read G25 and qpAdm results for an Assyrian genome.

f2, f3, f4 and D-statistics are the shared-drift arithmetic beneath qpAdm, qpWave and admixture graphs. What each statistic measures, how a four-population test works, and how to read Z-scores like the papers do.

From genotype files to a tested model: f2 extraction, qpadm() and its output tables, the arguments that silently change results (allsnps, fudge_twice, constrained), and the protocol discipline the code will not enforce for you.

Negative weights, SE 9.99, every model rejected, every model passing, infeasible popdrop rows, allsnps confusion — the standard failure gallery of qpAdm runs and what each symptom actually indicates.

qpAdm's sibling asks a prior question — how many independent streams of ancestry does a set of populations need? The rank test, cladality checks, and why every good qpAdm search starts with a qpWave answer.

The canonical nine outgroups from Lazaridis 2016, the o9a and o9aamcn extensions, the arithmetic floor and the ~30-population ceiling, and the published example where one added outgroup cut standard errors threefold.

The rotating protocol tests every candidate as source and outgroup in turn — elegant, recommended by the method's auditors, and carrying a measured 72–100% false-discovery rate when run without temporal discipline. What rotation is actually for.

Whether your sources predate your target is not a style preference — measured false-discovery rates run 16–31% for temporally stratified protocols and 72–100% for proximal rotating screens. What each model type is for.

The number that governs a qpAdm model is never your file's marker count — it is the intersection with the ancient panel, per statistic. The published coverage numbers, the allsnps table, and what a consumer chip can honestly support.

ADMIXTURE describes structure with K inferred components; qpAdm tests an explicit historical model and can reject it. What each estimates, why papers use both, and which answers which of your questions.

qpAdm first appeared in the supplement of the 2015 steppe-migration paper and became the method behind a decade of ancestry headlines. Where it came from, what it settled, and how a decade of stress-testing sharpened its limits.

A step-by-step qpAdm tutorial: check your raw file, merge it into AADR v66, choose sources and outgroups, run it in the browser or in R, and read the result.

Every place that sells or offers qpAdm in 2026: hand-checked analyses, DIY tools and subscriptions, with inputs, reference data and price models side by side.

What a qpAdm analysis costs in 2026: four one-time tiers from 29.99 EUR, the add-ons, what does not change the price, and what a DIY subscription costs instead.

What an admixture calculator optimises, why it always answers, what a qpAdm model adds, when each is the right tool, and when qpAdm is not worth paying for.

How to choose qpAdm left and right populations: the classic outgroups, the drift rule, the rank test, temporal logic, proxy labels, rotation and a worked example.

What a qpAdm p-value below 0.05 does and does not mean, the five usual causes of a rejection, negative weights, low Z-scores, what to try next and when to stop.

An illustrative qpAdm report for one era, read from the model line through the weights, p-value, right set, nested models and rank test to the explanation.

How to download your 23andMe raw data, what the v3, v4 and v5 chips mean for coverage after the AADR merge, and what a qpAdm order does with the file.

How to download your AncestryDNA raw file, what the v1 and v2 chips mean for coverage after the AADR merge, the allele quirk, and what a qpAdm order does.

How to download your MyHeritage raw CSV, what its chip means for coverage after the AADR merge, the low-pass WGS note, and what a qpAdm order does.

What ancient genomes actually say about Jewish ancestry, why a consumer 'Ashkenazi Jewish' percentage answers a different question, and what a formal qpAdm model with a p-value shows for a Jewish genome.

Why Ashkenazi genomes read as their own category on consumer tests, what the medieval Erfurt genomes settled, and how a qpAdm model separates the Levantine and southern European halves of Ashkenazi ancestry.

What ancient DNA says about Sephardic ancestry across Turkey, the Balkans, North Africa and Iberia, why 'Sephardic' covers several different genetic histories, and how a qpAdm model separates the Levantine, Iberian and North African layers.

Why the Jewish communities of Mesopotamia, Persia and Kurdistan sit closest to the Bronze Age Levant, what the Iranian-related layer in their genomes is, and how a qpAdm model resolves a Mizrahi genome.

What ancient DNA says about the Yemenite Jewish community, the Himyarite question, and how a qpAdm model tests a Yemenite genome against the Canaanite and Arabian Peninsula sources.

What genome-wide and ancient DNA say about the Jewish communities of Dagestan, Azerbaijan, Georgia and Central Asia, their Persian-Jewish core and local admixture, and how a qpAdm model resolves them.

Who the Canaanites were genetically, who carries their ancestry today, and why the qpAdm source catalog now has a Canaanite (2000 - 1200 BC) population built from the Megiddo and Hazor genomes.

What consumer ancestry percentages measure for Jewish customers, why an 'Ashkenazi 99%' result is circular, what a formal qpAdm model shows instead, what the four tiers buy, and the honest limits: endogamy, drift and coverage.

What the full qpAdm model record in an Ancestrify report means — chi-square, degrees of freedom, f4 rank, SNP counts, jackknife blocks, 95% confidence intervals, the nested-model table and the rank test — and how to read the plain-text download.

What a qpAdm ancestry test actually does with your raw DNA file, what the report contains, what the four tiers buy and what they don't, and how to tell a formal model from a percentage generator.

A plain reading guide to the three numbers in every qpAdm result — what the p-value tests, what a standard error bounds, what a Z-score rules out — with worked examples and the mistakes that make a passing model wrong.

What a 23andMe or AncestryDNA ethnicity estimate measures, what an ancient-DNA ancestry test measures instead, why the two disagree by design, and how to run the second one on the raw file you already have.

Who the Western Steppe Herders were, how steppe ancestry spread across Europe and Asia after 3000 BC, what a 'steppe percentage' actually measures, and how to estimate yours with qpAdm or Global25 from a raw DNA file.

Who Europe's Mesolithic hunter-gatherers were — Western, Eastern and Caucasus — how their ancestry survived farming and the steppe migrations, and how to measure your hunter-gatherer share from a raw DNA file.

Who the Anatolian Neolithic farmers were, how their ancestry spread across Europe from 6500 BC and became the largest component in most southern Europeans, what 'early European farmer' means in a model, and how to measure your share.

How to run an ancient-DNA ancestry analysis from a whole-genome sequencing VCF — tellmeGen, Dante Labs, Nebula and similar — what happens to the file at upload, why it is converted to the panel's markers, and what changes versus a chip export.

How to run qpAdm on your own genome after a published report — choosing sources and outgroups, reading a rejection, testing nested models, and downloading the EIGENSTRAT bundle to reproduce everything on your own machine.

What the Allen Ancient DNA Resource is, who curates it, what a version like v66 contains, the difference between the 1240K and Human Origins panels, and how the dataset becomes the reference behind an ancient-DNA ancestry analysis.

Global25 fits your coordinate to a mixture and always returns percentages. qpAdm tests a model against allele-frequency statistics and can reject it. A practical comparison of when each one is the right instrument.

DNA from ancient Himera reveals a diverse 480 BCE Greek army, distant mercenaries, local soldiers and mobility across the Mediterranean.

The first whole genome from Old Kingdom Egypt reveals deep North African ancestry and an eastern Fertile Crescent connection—with major limits.

Ancient DNA traces Yamnaya ancestry to Caucasus–Lower Volga and Dnipro–Don populations before the great Bronze Age steppe expansion.

DNA from 13 early Tarim Basin mummies reveals a genetically isolated local population that adopted dairy, crops and technologies from neighbors.

Ten genomes from a Himalayan cave reveal a population that was half Tibetan-related and half North Indian-related, mixing from about 2800 years ago.

238 ancient genomes from the Southern Cone reveal a deep central Argentina lineage that persisted for thousands of years with little inward migration.

A 2026 ancient DNA study traces Albanian ancestry from Bronze and Iron Age West Balkan groups through Roman-era and medieval admixture.

Ancient Balkan DNA reveals Roman-era Anatolian mobility, mixed late-antique migrations and lasting ancestry linked to Slavic expansion.

The method, for readers who want the maths: what qpAdm computes, what the p-value, standard error and z-score each mean, why outgroup choice decides whether a model is worth anything, and how to read a rejection — with a worked example.

qpAdm modeling shows modern Anatolian Turks carrying ancestry from Neolithic farmers, Yamnaya, and later Iron Age to medieval populations, reflecting a complex mix of local and incoming ancestries.

qpAdm modeling shows modern Balkan populations carry varying proportions of Neolithic farmer and Bronze Age steppe ancestry, reflecting long-term regional continuity.

Recent ancient DNA research provides the first comprehensive view of the Picenes (Picentes), an Iron Age population of Central Italy along the Middle Adriatic coast. This study sheds light on their paternal lineages, ancestral composition, and genetic relationships with neighboring populations.