手法を比較

	集団混合解析	Coalescent Theory	LDブロック解析
分野	遺伝学	遺伝学	遺伝学
系統	Process / pipeline	Process / pipeline	Process / pipeline
提唱年	2009	1982	2002
提唱者	David Alexander & Jonathan Novembre	John Kingman	Shaun Gabriel & Eric Lander
種類	Clustering and inference method	Stochastic process model	Haplotype analysis method
原典	Alexander, D. H., Novembre, J., & Lange, K. (2009). Fast model-based estimation of ancestry in unrelated individuals. Genome Research, 19(9), 1655–1664.	Kingman, J. F. C. (1982). The coalescent. Stochastic Processes and their Applications, 13(3), 235–248.	Gabriel, S. B., Schaffner, S. F., Nguyen, H., Moore, J. M., Roy, J., Blumenstiel, B., & Lander, E. S. (2002). The structure of haplotype blocks in the human genome. Science, 296(5576), 2225–2229.
別名	Population structure inference, Ancestry analysis, ADMIXTURE	Kingman Coalescent, n-coalescent	Haplotype block analysis, LD mapping, Block structure analysis
関連	4	4	5
概要	Admixture analysis is a population genetics method that infers population structure and individual ancestry from multilocus genotype data. Originally developed by Pritchard, Stephens, and Donnelly (2000) and refined by Alexander, Novembre, and Lange (2009), admixture analysis reveals how genetic variation is distributed among populations and estimates the ancestry fractions of admixed individuals. This technique is essential for understanding human evolutionary history, detecting population stratification in genetic studies, and inferring individual ancestry.	Coalescent theory is a probabilistic framework that traces the genealogical history of DNA sequences backward in time to their most recent common ancestor. Developed by John Kingman in 1982, this method forms the foundation of modern population genetics, enabling researchers to understand demographic events, estimate genetic parameters, and reconstruct evolutionary histories from modern genetic data.	Linkage disequilibrium (LD) block analysis is a genomic method that partitions the human genome into distinct haplotype blocks—regions of limited recombination where variants are in strong statistical association. First systematically described by Gabriel and colleagues in 2002, this approach reveals the underlying structure of genetic variation and enables efficient genomic studies by reducing the number of variants needed to capture common diversity. LD block analysis forms the foundation of genome-wide association study (GWAS) design and modern population genetics.