基于全基因组数据的AISNP选和分类算法的系统分析,用于法医生物地理祖先推断
Meiming Cai1, Fanzhang Lei1, Man Chen1
1Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong, China.
Forensic science international
|March 28, 2024
概括
这项研究使用机器学习确定有效的祖先信息单核酸多态 (AISNPs) 来确定生物地理起源. 这些遗传标记精确地预测了大陆和东亚的祖先,有助于法医调查.
科学领域:
- 遗传学 遗传学 是一个
- 法医科学 法医科学 法医科学
- 人口遗传学 人口遗传学
背景情况:
- 生物地理祖先的识别对于法医案件和嫌疑人的识别至关重要.
- 祖先信息单核酸多态 (AISNPs) 是人口结构分析的有价值的遗传标记.
研究的目的:
- 为准确的生物地理祖先推断开发一个有效的AISNP小组.
- 为了澄清人口遗传结构在各大洲和东亚的差异化.
主要方法:
- 利用了1000个基因组项目第三阶段 (26个种群) 的数据.
- 使用随机森林模型与嵌入式特征选择来识别高效的AISNP.
- 使用XGBoost与选定的AISNPs构建了祖先预测模型.
主要成果:
- 选择了58个AISNPs,将26个种群分为六个洲际祖先组成部分.
- 确定了24个特定于大陆和34个特定于东亚的AISNP.
- 在祖先预测模型中实现了高精度 (0.94-0.94) 和马修斯相关系数 (0.94-0.89).
结论:
- 使用特定人群AISNP的机器学习模型准确地预测了大陆和东亚内部的祖先起源.
- 使用高性能AISNP的分层推断系统可以将洲际种群与本地亚种群区分开来.
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