Evaluation of sample size effect on the identification of haplotype blocks

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 θ 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. Conclusion: 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

Evaluation of sample size effect on the identification of haplotype blocks

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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 <it>θ </it>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.</p> <p>Conclusion</p> <p>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.</p

Lack of association of genetic variation in chromosome region 15q14-22.1 with type 2 diabetes in a Japanese population

Background: Chromosome 15q14-22.1 has been linked to type 2 diabetes (T2D) and its related traits in Japanese and other populations. The presence of T2D disease susceptibility variant(s) was assessed in the 21.8 Mb region between D15S118 and D15S117 in a Japanese population using a region-wide case-control association test. Methods: A two-stage association test was performed using Japanese subjects: The discovery panel (Stage 1) used 372 cases and 360 controls, while an independent replication panel (Stage 2) used 532 cases and 530 controls. A total of 1,317 evenly-spaced, common SNP markers with minor allele frequencies > 0.10 were typed for each stage. Captured genetic variation was examined in HapMap JPT SNPs, and a haplotype-based association test was performed. Results: SNP2140 (rs2412747) (C/T) in intron 33 of the ubiquitin protein ligase E3 component n-recognin 1 (UBR1) gene was selected as a landmark SNP based on repeated significant associations in Stage 1 and Stage 2. However, the marginal p value (p = 0.0043 in the allelic test, OR = 1.26, 95% CI = 1.07–1.48 for combined samples) was weak in a single locus or haplotype-based association test. We failed to find any significant SNPs after correcting for multiple testing. Conclusion: The two-stage association test did not reveal a strong association between T2D and any common variants on chromosome 15q14-22.1 in 1,794 Japanese subjects. A further association test with a larger sample size and denser SNP markers is required to confirm these observations

Lack of association of genetic variation in chromosome region 15q14-22.1 with type 2 diabetes in a Japanese population

<p>Abstract</p> <p>Background</p> <p>Chromosome 15q14-22.1 has been linked to type 2 diabetes (T2D) and its related traits in Japanese and other populations. The presence of T2D disease susceptibility variant(s) was assessed in the 21.8 Mb region between <it>D15S118 </it>and <it>D15S117 </it>in a Japanese population using a region-wide case-control association test.</p> <p>Methods</p> <p>A two-stage association test was performed using Japanese subjects: The discovery panel (Stage 1) used 372 cases and 360 controls, while an independent replication panel (Stage 2) used 532 cases and 530 controls. A total of 1,317 evenly-spaced, common SNP markers with minor allele frequencies > 0.10 were typed for each stage. Captured genetic variation was examined in HapMap JPT SNPs, and a haplotype-based association test was performed.</p> <p>Results</p> <p>SNP2140 (rs2412747) (<it>C/T</it>) in intron 33 of the ubiquitin protein ligase E3 component n-recognin 1 (<it>UBR1</it>) gene was selected as a landmark SNP based on repeated significant associations in Stage 1 and Stage 2. However, the marginal <it>p </it>value (<it>p </it>= 0.0043 in the allelic test, OR = 1.26, 95% CI = 1.07–1.48 for combined samples) was weak in a single locus or haplotype-based association test. We failed to find any significant SNPs after correcting for multiple testing.</p> <p>Conclusion</p> <p>The two-stage association test did not reveal a strong association between T2D and any common variants on chromosome 15q14-22.1 in 1,794 Japanese subjects. A further association test with a larger sample size and denser SNP markers is required to confirm these observations.</p

The effect of the number of simulation repeats on haplotype block characteristics under different block definitions: profiles versus the number of repeat times ()

<p><b>Copyright information:</b></p><p>Taken from "Evaluation of sample size effect on the identification of haplotype blocks"</p><p>http://www.biomedcentral.com/1471-2105/8/200</p><p>BMC Bioinformatics 2007;8():200-200.</p><p>Published online 14 Jun 2007</p><p>PMCID:PMC1913927.</p><p></p> The sample size () was adjusted by fixing it at 725 (solid lines) or 50 (dashed lines). The labels of analyzed SNPs intervals are identical to those in Figure 1. The number of repeat times () is shown on the horizontal axis. The simulation was repeated 10,000 times (= 10,000) from 1, 100, 500, 1,000, 2,000, 3,000, 4,000, 5,000, and 7,500 times. profiles (the ratio of times to times when simulating the transition zone of haplotype block) are shown on the vertical axis. The three labels represent different haplotype block definitions: blue square, Kamatani's method; green triangle, Gabriel's method; red diamond, four-gamete test

Lack of association of genetic variation in chromosome region 15q14-22.1 with type 2 diabetes in a Japanese population-0

Ap JPT database, and distribution of 29,728 SNPs in HapMap JPT (10) in every 300-kb bin against the physical distance in the target region. Number of tag SNPs (r> 0.7, 0.8, and 0.9) found for this study matched with the r> 0.7, 0.8, and 0.9 SNPs in HapMap JPT (4, 5, and 6) and number of tag SNPs (r> 0.7, 0.8, and 0.9) among the HapMap JPT SNPs (7, 8, and 9). The vertical bars in the top panel show the position of RefSeq genes in this region.<p><b>Copyright information:</b></p><p>Taken from "Lack of association of genetic variation in chromosome region 15q14-22.1 with type 2 diabetes in a Japanese population"</p><p>http://www.biomedcentral.com/1471-2350/9/22</p><p>BMC Medical Genetics 2008;9():22-22.</p><p>Published online 27 Mar 2008</p><p>PMCID:PMC2324080.</p><p></p

Lack of association of genetic variation in chromosome region 15q14-22.1 with type 2 diabetes in a Japanese population-1

N chromosome 15q14-22.1 in the Japanese and other ethnic populations. The solid and open circles denote LOD scores and location in recombination distance. The width of the straight lines or a broken line denote a 1-LOD drop interval when available. The vertical bars show the positions of RefSeq genes (upper) and the 1,317 chosen SNPs (lower) with black vertical bars placed in gene-centric regions and gray vertical bars in intergenic regions. Allelic values in Stage 1 (372 cases and 360 controls) for 1,317 SNPs (A), in Stage 2 (532 cases and 530 controls) for 112 SNPs (B), and in Stage 1 + Stage 2 combined samples (904 cases and 890 controls) for one replicated SNP (C) were plotted against physical positions. The data denote the -log , and = 0.05 is shown with a thick line. The landmark SNP2140 (rs2412747) is indicated with an arrow.<p><b>Copyright information:</b></p><p>Taken from "Lack of association of genetic variation in chromosome region 15q14-22.1 with type 2 diabetes in a Japanese population"</p><p>http://www.biomedcentral.com/1471-2350/9/22</p><p>BMC Medical Genetics 2008;9():22-22.</p><p>Published online 27 Mar 2008</p><p>PMCID:PMC2324080.</p><p></p