Estimation of Haplotype Frequencies, Linkage-Disequilibrium Measures, and Combination of Haplotype Copies in Each Pool by Use of Pooled DNA Data

• Published in: American journal of human genetics Vol. 72; no. 2; pp. 384 - 398
• Main Authors: Ito, Toshikazu, Chiku, Suenori, Inoue, Eisuke, Tomita, Makoto, Morisaki, Takayuki, Morisaki, Hiroko, Kamatani, Naoyuki
• Format: Journal Article
• Language: English
• Published: Chicago, IL Elsevier Inc 01.02.2003; University of Chicago Press; The American Society of Human Genetics
• Subjects: Algorithms; Alleles; Biological and medical sciences; Carrier Proteins - genetics; Classical genetics, quantitative genetics, hybrids; Computer Simulation; Cytoskeletal Proteins - genetics; Fundamental and applied biological sciences. Psychology; Gene Frequency - genetics; Genetic Linkage; Genetics of eukaryotes. Biological and molecular evolution; Genetics, Population; Genotype; Haplotypes - genetics; Human; Humans; Likelihood Functions; Linkage Disequilibrium - genetics; Lod Score; Methylenetetrahydrofolate Reductase (NADPH2); Muscle Proteins - genetics; Oxidoreductases Acting on CH-NH Group Donors - genetics; Polymorphism, Single Nucleotide; Serum Amyloid A Protein - genetics; Statistical analysis; Linkage; DNA; Estimation; Frequency; Genetics; Linkage equilibrium; Algorithm; Haplotype
• ISSN: 0002-9297; 1537-6605
• DOI: 10.1086/346116

Inference of haplotypes is important for many genetic approaches, including the process of assigning a phenotype to a genetic region. Usually, the population frequencies of haplotypes, as well as the diplotype configuration of each subject, are estimated from a set of genotypes of the subjects in a sample from the population. We have developed an algorithm to infer haplotype frequencies and the combination of haplotype copies in each pool by using pooled DNA data. The input data are the genotypes in pooled DNA samples, each of which contains the quantitative genotype data from one to six subjects. The algorithm infers by the maximum-likelihood method both frequencies of the haplotypes in the population and the combination of haplotype copies in each pool by an expectation-maximization algorithm. The algorithm was implemented in the computer program LDPooled. We also used the bootstrap method to calculate the standard errors of the estimated haplotype frequencies. Using this program, we analyzed the published genotype data for the SAA ( n=156), MTHFR ( n=80), and NAT2 ( n=116) genes, as well as the smoothelin gene ( n=102). Our study has shown that the frequencies of major (frequency >0.1 in a population) haplotypes can be inferred rather accurately from the pooled DNA data by the maximum-likelihood method, although with some limitations. The estimated D and D′ values had large variations except when |D| values were >0.1. The estimated linkage-disequilibrium measure ρ 2 for 36 linked loci of the smoothelin gene when one- and two-subject pool protocols were used suggested that the gross pattern of the distribution of the measure can be reproduced using the two-subject pool data.