حاسبة التركيب الجيني

MDLP K7 World

MDLP K7 World is a seven-component admixture calculator that estimates African, Siberian, Indian, Papuan, European, Southeast Asian (SEA), and Amerindian ancestry proportions. Designed for global users — from genealogists to population researchers — it offers an accessible, comparative view of deep and recent ancestry, useful for cross-population comparisons, education, and exploratory research.

7 المكوّنات
العالم المنطقة المستهدفة
MDLP المؤلف
حديثة الفترة
مرّر لاستكشاف الصفحة
الفصل الأول

تفاصيل الحاسبة

معلومات عن حاسبة التركيب الجيني

M

MDLP

منشئ الحاسبة

نبذة عن الحاسبة

MDLP K7 World is a reference-based genetic admixture calculator that estimates the proportionate contributions of seven broad ancestral sources — African, Siberian, Indian, Papuan, European, Southeast Asian (SEA), and Amerindian — to an individual genome. Built for users worldwide, it is designed for genealogy enthusiasts, anthropologists, population geneticists, and curious individuals seeking a clear, comparative snapshot of deep and recent ancestry across global regions.

The calculator analyzes genome-wide markers against curated reference populations to produce a seven-component profile that highlights major continental and subcontinental affiliations. Results reveal admixture proportions, emphasize major migratory legacies (for example Out-of-Africa dispersals, Eurasian diversification, Austronesian and Papuan expansions, South Asian genetic formation, and the peopling of the Americas), and can suggest whether a sample reflects mostly single-region ancestry or complex multi-regional mixtures. Visual outputs map components into intuitive percentages that can be compared across individuals and populations.

MDLP K7 World is valuable because it balances interpretability and global coverage: seven components keep results accessible while capturing key genetic structure relevant to worldwide populations. It is particularly useful for cross-population comparisons, educational contexts, and preliminary research where a compact, reproducible admixture breakdown is preferred. Users should understand this is a broad-resolution tool — it provides robust continental-level insight but is not a substitute for fine-scale, region-specific analyses or clinical interpretation. When combined with historical records, linguistic data, and archaeology, MDLP K7 World helps illuminate personal and population histories, offering a concise window into how ancient migrations and local interactions shaped present-day genomes.

الفصل الثاني

المجموعات السكانية المرجعية

المجموعات السكانية التي تستخدمها الحاسبة كمراجع جينية

7 مجموعة سكانية مرجعية

  • African: Explore the African ancestry component, which spans the vast continent known for its epic landscapes and incredible biodiversity. From the ancient pyramids of Egypt to the sweeping savannas of the Serengeti and the vibrant cultures of West Africa, this genetic heritage is a mosaic of human history, innovation, and enduring spirit.

  • Siberian: Delve into the Siberian ancestry component, where the vast, icy expanses of northern Asia have been home to resilient nomadic tribes. This lineage tells the story of people adapted to some of the planet's most extreme conditions, their cultures woven into the fabric of the Arctic and sub-Arctic regions known for their stark beauty and dramatic climates.

  • Indian: Discover the Indian ancestry component, a rich blend of dynasties, languages, and religions that has flourished on the Indian subcontinent. From the spiritual banks of the Ganges to the majestic peaks of the Himalayas, this genetic lineage embodies the diversity and complexity of cultures that have contributed significantly to global civilization.

  • Papuan: Investigate the Papuan ancestry component, representative of the indigenous peoples of New Guinea and surrounding islands. This heritage echoes the lives of communities that have navigated dense rainforests and mountainous terrains, maintaining traditions that date back thousands of years in one of the world's most linguistically diverse regions.

  • European: Engage with the European ancestry component, which encapsulates a wide range of historical epochs, from the ancient Greco-Roman civilizations to the medieval kingdoms and modern innovations. This genetic legacy traverses the cultural and artistic achievements that have profoundly shaped Western philosophy, science, and art.

  • SEA (Southeast Asian): Immerse yourself in the Southeast Asian ancestry component, characterized by its vibrant cultures and histories of maritime trading kingdoms and colonial interactions. This lineage encompasses the warm waters of the South China Sea to the island chains of Indonesia and the Philippines, spotlighting a region known for its tropical diversity and culinary richness.

  • Amerindian: Reflect on the Amerindian ancestry component, which represents the first peoples of the Americas, from the Arctic tundra of Canada to the forests of the Amazon and the high plains of the Andes. This heritage reveals millennia of adaptation and innovation in diverse environments, offering insights into a profound connection with the natural world and a complex pre-Columbian history.

الفصل الثالث

فهم تحليل التركيب الجيني

تعرّف على طريقة عمل الحاسبات وكيفية تفسير نتائجها

ما تحليل التركيب الجيني؟

يقارن تحليل التركيب الجيني حمضك النووي ببيانات مجموعات سكانية مرجعية من أنحاء العالم. ويقدّر مدى التشابه مع المكوّنات المرجعية التي يتألف منها النموذج.

تستخدم الحاسبة 7 من المجموعات السكانية المرجعية المختارة بعناية لاستكشاف أوجه التشابه الجيني.

كيف يعمل التحليل؟

  • يقارن التحليل حمضك النووي بعدد 7 من المجموعات السكانية المرجعية
  • يستخدم التحليل مجموعات سكانية مرجعية من الفترات المعروضة.
  • توضّح النتائج مدى التشابه الجيني مع هذه المجموعات
  • تؤثر ملاءمة المراجع وتنوّعها في جودة المقارنة

فهم النتائج

تعرض النتائج نسبًا مقدّرة ضمن نموذج المقارنة بالمجموعات المرجعية. ضع النقاط التالية في الاعتبار:

  • تعبّر النتائج عن التشابه الجيني ولا تثبت النسب المباشر
  • تعتمد المقارنة على المجموعات المرجعية المدرجة في الحاسبة.
  • تبيّن النسب الوزن النسبي لكل مكوّن في النموذج
  • النتائج تقديرات تستند إلى البيانات المرجعية المتاحة