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Effects of cutoff thresholds for minor allele frequencies on HapMap resolution: A real dataset-based evaluation of the Chinese Han and Tibetan populations

DOI: 10.1007/s11434-009-0302-4

Keywords: HapMap,MAF cutoff threshold,HapMap resolution

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Abstract:

Genomic variation is the genetic basis of phenotypic diversity among individuals, including variation in disease susceptibility and drug response. The greatest promise of the International HapMap is to provide roadmaps for identifying genetic variants predisposing to complex diseases. Single nucleotide polymorphism (SNP) is the fundamental element of the HapMap. Allele frequency of SNPs is one of the major factors affecting the resulting HapMap, being the factor upon which linkage disequilibrium (LD) is calculated, haplotypes are constructed, and tagging SNPs (tagSNPs) are selected. The cutoff thresholds for the frequency of minor alleles used in the making of the map therefore have profound effects on the resolution of that map. To date most researchers have adopted their own cutoff thresholds, and there has been little real dataset-based evaluation of the effects of different cutoff thresholds on HapMap resolution. In an attempt to assess the implications of different cutoff values, we analyzed our own data for the centromeric genes on Chromosome 15 in Chinese Han and Tibetan populations, with respect to minor allele frequency cutoff values of ≥0.01 (0.01 group), ≥0.05 (0.05 group), and ≥0.10 (0.10 group), and constructed HapMaps from each of the datasets. The resolution, study power and cost-effectiveness for each of the maps were compared. Our results show that the 0.01 threshold provides the greatest power (P = 0.019 in Han and P = 0.029 in Tibetan for 0.01 vs. 0.05 threshold) and detects most population-specific haploypes (P = 0.012 for 0.01 vs. 0.05 threshold). However, in the regions studied, the 0.05 cutoff threshold did not significantly increase power above the 0.10 threshold (P = 0.191 in Han; 1.000 in Tibetans), and did not improve resolution over the 0.10 value for populationspecific haplotypes (P = 0.592) neither. Furthermore the 0.05 and 0.10 values produced the same figures for tagging efficiency, LD block number, LD length, study power and cost-savings in the Tibetan population. These results suggest that a lower cutoff value is more appropriate for studies in which population-specific haplotypes are crucial, and that the most appropriate cutoff value may differ between populations. Due to the limited genes studied in this project more studies should be conducted to further address this important issue.

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