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Biases and reconciliation in estimates of linkage disequilibrium in the human genome.

Abstract：

:Genetic association studies of common disease often rely on linkage disequilibrium (LD) along the human genome and in the population under study. Although understanding the characteristics of this correlation has been the focus of many large-scale surveys (culminating in genomewide haplotype maps), the results of different studies have yielded wide-ranging estimates. Since understanding these differences (and whether they can be reconciled) has important implications for whole-genome association studies, in this article we dissect biases in these estimations that are due to known aspects of study design and analytic methodology. In particular, we document in the empirical data that the long-known complicating effects of allele frequency, marker density, and sample size largely reconcile all large-scale surveys. Two exceptions are an underappraisal of redundancy among single-nucleotide polymorphisms (SNPs) when evaluation is limited to short regions (as in candidate-gene resequencing studies) and an inflation in the extent of LD in HapMap phase I, which is likely due to oversampling of specific haplotypes in the creation of the public SNP map. Understanding these factors can guide the understanding of empirical LD surveys and has implications for genetic association studies.

journal_name

Am J Hum Genet

journal_title

American journal of human genetics

authors

Pe'er I,Chretien YR,de Bakker PI,Barrett JC,Daly MJ,Altshuler DM

doi

10.1086/502803

subject

Has Abstract

pub_date

2006-04-01 00:00:00

pages

588-603

issue

4

eissn

0002-9297

issn

1537-6605

pii

S0002-9297(07)63698-2

journal_volume

78

pub_type

杂志文章

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