title: Evaluation of sample size effect on the identification of haplotype blocks.
abstract: BACKGROUND
  Genome-wide maps of linkage disequilibrium (LD) and haplotypes have been created for different populations. Substantial sharing of the boundaries and haplotypes among populations was observed, but haplotype variations have also been reported across populations. Conflicting observations on the extent and distribution of haplotypes require careful examination. The mechanisms that shape haplotypes have not been fully explored, although the effect of sample size has been implicated. We present a close examination of the effect of sample size on haplotype blocks using an original computational simulation.
  
  
  RESULTS
  A region spanning 19.31 Mb on chromosome 20q was genotyped for 1,147 SNPs in 725 Japanese subjects. One region of 445 kb exhibiting a single strong LD value (average |D'|; 0.94) was selected for the analysis of sample size effect on haplotype structure. Three different block definitions (recombination-based, LD-based, and diversity-based) were exploited to create simulations for block identification with theta value from real genotyping data. As a result, it was quite difficult to estimate a haplotype block for data with less than 200 samples. Attainment of a reliable haplotype structure with 50 samples was not possible, although the simulation was repeated 10,000 times.
  
  
  CONCLUSIONS
  These analyses underscored the difficulties of estimating haplotype blocks. To acquire a reliable result, it would be necessary to increase sample size more than 725 and to repeat the simulation 3,000 times. Even in one genomic region showing a high LD value, the haplotype block might be fragile. We emphasize the importance of applying careful confidence measures when using the estimated haplotype structure in biomedical research.
authors.affiliation: Department of Bioinformatics, Division of Life Science Systems, Fujitsu Limited, Higashishinbashi, Minato-ku, Tokyo, Japan. d_osabe@jp.fujitsu.com <d_osabe@jp.fujitsu.com>
authors.forename: Dai
authors.initials: D
authors.lastname: Osabe
authors.forename: Toshihito
authors.initials: T
authors.lastname: Tanahashi
authors.forename: Kyoko
authors.initials: K
authors.lastname: Nomura
authors.forename: Shuichi
authors.initials: S
authors.lastname: Shinohara
authors.forename: Naoto
authors.initials: N
authors.lastname: Nakamura
authors.forename: Toshikazu
authors.initials: T
authors.lastname: Yoshikawa
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Shiota
authors.forename: Parvaneh
authors.initials: P
authors.lastname: Keshavarz
authors.forename: Yuka
authors.initials: Y
authors.lastname: Yamaguchi
authors.forename: Kiyoshi
authors.initials: K
authors.lastname: Kunika
authors.forename: Maki
authors.initials: M
authors.lastname: Moritani
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Inoue
authors.forename: Mitsuo
authors.initials: M
authors.lastname: Itakura
mesh_terms: D002874:Chromosome Mapping / Q000379:methods*; D002890:Chromosomes, Human, Pair 20 / Q000235:genetics*; D003198:Computer Simulation; D014644:Genetic Variation / Q000235:genetics*; D006239:Haplotypes / Q000235:genetics*; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D018401:Sample Size; D012680:Sensitivity and Specificity