MDLP K16c
MDLP K16c (Ancient) estimates proportions of 16 deep-time ancestral components using ancient reference samples. Designed for worldwide users—researchers and enthusiasts—it highlights Neolithic farmer, Steppe, Paleolithic hunter‑gatherer, Oceanian, and African signals. Use it to explore prehistoric migrations and population structure; results reflect long-term population history rather than recent genealogy.
Calculator Details
Comprehensive information about this admixture calculator
About This Calculator
Reference Populations
The populations used as genetic references in this calculator
16 Reference Populations
SEA (Southeast Asia)
- Populations in this region are diverse, with influences from Austronesian, Austroasiatic, and Sino-Tibetan ethnic groups.
CHG (Caucasus Hunter-Gatherers)
- Ancient populations from the Caucasus region, known to have contributed to the genetic makeup of various Eurasian groups.
Steppe_EMBA (Early to Middle Bronze Age Steppe)
- Nomadic pastoralist populations from the Eurasian Steppe during the Early to Middle Bronze Age, associated with the spread of Indo-European languages.
Mota
- An ancient African individual from Ethiopia, providing insights into the genetic history of East Africa.
ElMiron
- Represents populations from Upper Paleolithic Europe, specifically associated with the Magdalenian culture.
Anatolia_N (Neolithic Anatolia)
- Early farming populations from Anatolia, pivotal in the spread of agriculture into Europe.
Papuan
- Indigenous populations of Papua New Guinea, characterized by ancient lineages distinct from mainland Asians.
Steppe_Eneolithic (Eneolithic Steppe)
- Populations from the Eurasian Steppe during the Eneolithic (Copper Age), crucial in Bronze Age migrations.
Onge
- Indigenous people of the Andaman Islands, representing one of the earliest modern human groups in Southeast Asia.
Europe_LNBA (Late Neolithic to Bronze Age Europe)
- Populations in Europe during the transition from the Neolithic to the Bronze Age, marked by significant cultural and genetic changes.
ANE (Ancient North Eurasian)
- Ancient populations from Siberia, contributing to the genetic ancestry of Native Americans and other groups.
Europe_MNChL (Middle to Late Neolithic and Chalcolithic Europe)
- Farming communities in Europe during the Middle to Late Neolithic and Chalcolithic periods, prior to the arrival of Steppe migrants.
Paleoafrican
- Ancient African lineages with deep historical roots on the continent.
Biaka
- Indigenous populations of Central Africa, part of the Pygmy groups with a unique genetic heritage.
EA (East Asia)
- Diverse populations from East Asia, encompassing a variety of ethnic groups and genetic makeups.
Villabruna
- An Upper Paleolithic individual from Italy, representing European hunter-gatherer ancestry.
Grouped by Continent
Africa
- Mota, Paleoafrican, Biaka
Asia
- SEA, Papuan, Onge, EA
Europe
- ElMiron, Anatolia_N, Europe_LNBA, Europe_MNChL, Villabruna
Eurasian Steppe
- Steppe_EMBA, Steppe_Eneolithic, CHG
North Eurasia
- ANE
Understanding Admixture Analysis
Learn how admixture calculators work and how to interpret your results
What is Admixture Analysis?
Admixture analysis is a method used to estimate your genetic ancestry by comparing your DNA to reference populations from around the world. Think of it as creating a recipe of your genetic makeup, where the ingredients are different ancestral populations.
This calculator uses 16 carefully selected ancient populations as references, allowing for a detailed breakdown of your genetic heritage.
How It Works
- Your DNA is compared to 16 reference populations
- Ancient populations are used as genetic references
- Results show your genetic similarity to these populations
- More accurate with a diverse reference panel
Understanding Your Results
Your results will show percentages of genetic similarity to these reference populations. Remember these important points:
- Results reflect genetic similarity, not direct ancestry
- Ancient populations are used as references
- Percentages indicate relative genetic contribution
- Results are estimates based on available reference data