
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.
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Methodology deep-dives, population spotlights, and engineering notes from the Ancestrify team, qpAdm modelling, ancient DNA panels, and how genetic ancestry analysis really works.

Turkish ancestry through ancient DNA: the Anatolian farmer substrate, the Southern Arc results, Byzantine Anatolia, the modest Turkic layer and qpAdm.
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167 stories

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.

Every service that sells or offers a Global25 (G25) analysis in 2026, side by side: what each computes, whether the coordinates are official, whether the source panels are published, whether anyone builds a calculator around your own row, and the price model as each site states it.

Every place that sells, obtains or simulates Global25 (G25) coordinates in 2026, side by side: the official portal, the done-for-you route, derived rows and free simulations, with prices as each site states them.

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.

A new Science Advances study sequences the largest Jomon dataset yet: where Japan's ancient foragers came from, the cold-adaptation selection written in their genomes, and what their legacy means for reading Japanese ancestry.

A new 30-genome transect of southwestern England confirms the sharp Beaker-era turnover — and shows the genetically distinct newcomers burying their dead inside monuments built a millennium earlier by the people they replaced.

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.

Looking for a MyTrueAncestry alternative? What people actually want from one — individual ancient matches, published statistics, one-time pricing — and which services deliver each, honestly compared.

The complete Global25 price list: what official coordinates cost, what is genuinely free, what a worked analysis and its add-ons cost, and the traps that make 'free G25' expensive.

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.

The fit distance measures how far a mixture still sits from your coordinate — not whether the model is right. Calibrated bands for reading one, why lower stops being better, and the checks that actually validate a model.

Every Global25 row exists in two forms, and mixing them is the hobby's most common silent error. What scaling does mathematically, which form each tool expects, and the tell-tale signs of a mixed comparison.

Adding sources always lowers a G25 fit distance and routinely worsens the model — a worked demonstration where the fit improved from 0.0110 to 0.0068 while the story collapsed. The rules that keep a panel honest.

Global25 is a projection, not a test — so 'accuracy' has layers: the coordinate's own fidelity, the references it is compared against, and the models built on top. An honest audit of all three.

Ger Huijbregts's nMonte turned Global25 rows into ancestry percentages and founded a whole tool tradition. How the Monte-Carlo search works, what nMonte3 changed, what the fit distance is, and the discipline the script never enforces.

What a Global25 PCA projection shows, what the axes are and are not, why plot distance lies, the difference between projecting onto a fixed view and fitting your own — and the honest uses of both.

A Global25 model and a testing company's ethnicity estimate answer different questions with different references and different time depths. What each is actually computing, and which to trust for which claim.

Everything you can do with a Global25 row without paying anyone: distance rankings, admixture fits, PCA plots, averaging, authenticity checks — Vahaduo, nMonte and the Ancestrify Lab, honestly compared.

Dante Labs, Nebula, Sequencing.com and other WGS files can become official Global25 coordinates — via the portal's own conversion surcharge or a free WGSExtract conversion. What each route costs and where the traps are.

What a Global25 distance ranking actually measures, why era choice changes everything, how close is 'close', and the four misreadings that turn a good tool into a wrong conclusion.

From the Eurogenes blog's admixture calculators through Global 10 to the 2018 launch of Global25 — why a 25-dimension PCA became the ancestry community's common currency, and what changed around it since.

Every admixture calculator — GEDmatch's classics, Global25 fits, testing-company estimates — is an optimiser that cannot say no. How the three families work, what the percentages mean, and the questions a calculator can and cannot answer.

Which GEDmatch admixture project to run for your background, what each calculator's components mean, why the projects disagree with each other, and what has aged since 2012–2016.

There is no single best admixture calculator — there is a best one per question. An honest decision guide across GEDmatch's classics, Global25 tools and formal methods, from someone who builds one of them.

Accuracy has three different meanings for an ancestry calculator, and the tools do well on exactly one of them. Where percentages are trustworthy, where they are noise, and how to tell which regime you are in.

The same genome scores 44% North European in one calculator and 51% in another. Component anchoring, reference panels, the calculator effect and K explain the spread — and none of the numbers is 'the real one'.

Oracle ranks reference populations by how closely their calculator percentages match yours — not by shared DNA. How the distance is computed, what single and mixed modes tell you, and the misreadings to avoid.

The thirteen K13 components, what North Atlantic, East Med and West Asian are anchored to, who the calculator works best for, how to read the Oracle — and the caveats that come with a 2012-era tool.

What the 36-component Eurogenes calculator can genuinely show, why its regional labels invite over-reading, what a K36 heat map is actually plotting, and when a distance ranking answers the question better.

The original admixture project's most-used calculator: what the twelve K12b components are anchored to, what Gedrosia and Caucasus mean in modern ancient-DNA terms, and how to read a K12b breakdown.

What HarappaWorld's S-Indian, Baloch and NE-Euro components are anchored to, why it remains the reference calculator for South Asian ancestry, and how its 2012 categories map onto what ancient DNA later proved.

The program behind the bar plots in population-genetics papers: how ADMIXTURE estimates K components jointly from all samples, supervised versus unsupervised runs, choosing K, and why hobbyist calculators are its frozen shadows.

A calculator against modern populations answers 'who do I resemble today'; one against dated ancient samples answers 'which deep ancestries formed me'. Mixing up the two produces the classic misreadings.

GEDmatch's admixture calculators froze around 2012–2016. The free alternatives that run on current ancient reference panels — era-scoped calculators, distance rankings, PCA — and what each replaces.

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 Davidski's Eurogenes G25 Requests portal is, what you upload, the scaled and unscaled rows you get back, their stated fee, and what to do with the row next.

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.

Global25 coordinates explained from scratch: what the 25 numbers are, where they come from, scaled versus unscaled, what you can compute from them, and the honest limits of a coordinate-based ancestry analysis.

A step-by-step Vahaduo tutorial: where to paste your Global25 coordinates, how the Distance, Single, Multi and PCA tabs work, how to build a source panel, and how to read a fit distance without over-reading it.

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.

What a maternal (mtDNA) haplogroup is, how the tree is built, what H, U5, K, T2 and the other common branches tell you, why most chip kits resolve to a broad branch, and what a haplogroup can and cannot say about ancestry.

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.

Why a standard Global25 calculator can describe a population well and one person badly, how an analyst hand-builds a source panel around your own coordinates, and what changes in the report when a personalised calculator is published beside the standard one.

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.

What it means to share a stretch of DNA with a person who died thousands of years ago, why such matches are identity by state rather than identity by descent, what the centimorgan figures mean, and why a shared segment is never proof of descent.

Notable Matches ranks your Global25 coordinates against 172 famous ancient individuals with published DNA — kings, mummies, warriors and Ice Age people. What a distance to one buried person means, and what it can never mean.

What a Y-DNA haplogroup actually is, how to export the raw file from 23andMe, AncestryDNA or MyHeritage, how to get a free and honest paternal haplogroup call from it, and where to explore your branch afterwards.

What mitochondrial DNA records, how to get a free maternal haplogroup call from a 23andMe, AncestryDNA or MyHeritage export, why most chip kits resolve to a broad branch, and how to explore the maternal tree afterwards.

Two new free tools: browse the complete paternal tree — over 109,000 named branches — and the full maternal tree, with defining variants, tester counts by country and search by haplogroup or SNP. No account needed.

You can now start a G25 analysis from the raw DNA file you already have — with your consent, we obtain your official Global25 coordinates from the independent provider for €15, and your full analysis runs the moment they arrive.

23andMe does not produce G25 coordinates — but its raw data file is a good starting point. How to download it, what the v5 chip actually covers, and the exact route from file to coordinate row.

AncestryDNA does not produce G25 coordinates — but its raw data download is the input that becomes one. The emailed-confirmation download flow, what the file covers, and the route from file to coordinate row.

MyHeritage does not produce G25 coordinates — but its raw data export is the input that becomes one. The download flow, the low-pass WGS caveat that costs people their haplogroups, and the route to a coordinate row.

FamilyTreeDNA does not produce G25 coordinates — but a Family Finder raw data export is the input that becomes one. Which download to pick, what the file covers, and the route to a coordinate row.

LivingDNA does not produce G25 coordinates — but its raw data download is the input that becomes one. Where the download lives, what the file covers, and the route to a coordinate row.

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.

What the 25 numbers mean, why scaled and unscaled forms must never be mixed, how a closest-population ranking is computed, what a fit distance does and does not tell you, and the failure modes that make confident results wrong.

Where Global25 coordinates come from, how to get them whether you tested with 23andMe, AncestryDNA, MyHeritage, FamilyTreeDNA or LivingDNA, and how to tell a real coordinate row from a simulated one.

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 reveals that Punic communities shared Phoenician culture but drew most sampled ancestry from Sicily, the Aegean and North Africa.

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

DNA from 102 prehistoric Aegeans traces migration into Crete and Greece, Mycenaean-era mobility, family burials and frequent cousin unions.

A 555-genome study traces large-scale Early Medieval migration associated with Slavic expansion, regional admixture and changing communities.

Ancient DNA connects some European Huns to Xiongnu elite lineages while revealing a highly diverse Carpathian Basin population.

Genomes from Ranis and Zlatý kůň date the shared Neanderthal admixture in ancestors of non-Africans to roughly 45,000–49,000 years ago.

DNA from Iron Age Britain reveals matrilocal communities, female-line descent and continuing migration across the English Channel.

A 258-genome study reveals migration, Roman provincial mobility and family life along southern Germany's frontier after imperial rule.

Ancient Etruscan DNA supports local Iron Age origins, genetic similarity to Latin neighbors and major ancestry shifts under imperial Rome.

Ancient DNA reconstructs Avar-period families, marriage networks and neighboring communities with different ancestry across Central Europe.

Fifteen ancient Rapanui genomes challenge a severe pre-European collapse and date Indigenous American-related ancestry to 1250–1430 CE.

DNA from two women at Takarkori reveals a deeply rooted North African lineage and suggests Saharan pastoralism spread mainly through culture.

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

A 460-genome study reveals large North Sea migration, local integration and regional ancestry change in Early Medieval England.

A study of 15,836 ancient and modern West Eurasians finds hundreds of genes under strong directional selection over the past ten thousand years.

A 200,000-year-old molar from Denisova Cave yields a second high-quality Denisovan genome and reveals at least three distinct Denisovan groups.

Ancient proteins and mitochondrial DNA from dental calculus identify the near-complete Harbin cranium from northeastern China as a Denisovan.

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.

Yersinia pestis genomes from four Siberian hunter-gatherer cemeteries show lethal plague outbreaks millennia before cities, farming or rats.

Ancient genomes of Mycobacterium lepromatosis from Canada and Argentina show a second leprosy pathogen circulating in the Americas before contact.

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

Picuris Pueblo initiated a genomic study of its own ancestors, showing continuity across a millennium and a firm link to Chaco Canyon.

Ancient DNA from five Pompeii plaster casts overturns the family stories told about them for more than a century.

Genomes from an 11,000-year-old site near Beijing reveal an unknown deep northern East Asian lineage and 2,000 years of change at one place.

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.

A 2023 Science study analyzed 161 languages, dated the Indo-European root to about 8,120 years ago, and proposed a debated hybrid origin.

A 442-genome Viking study reveals regional Scandinavian ancestry, family expeditions, migration and Viking identities beyond genetic ancestry.

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.

A 2026 study of 102 Deep Maniots finds unusual paternal isolation, Bronze Age-linked lineages, medieval founder effects and diverse maternal ancestry.

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.