Case-control analyses: Geneopardy!

Jorgenson, Eric; Liu, Xin; Witte, John S.

doi:10.1002/gepi.20114

Cited by 4 publications

(4 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This problem is well known since the early days of genetics [6] , but, nonetheless, has been largely ignored in genetic epidemiological research. The revived interest in the case-control study design using genetic markers has stirred a recent debate about the relevance of confounding by population substructure and admixture [7][8][9][10] with lack of empirical evidence, especially when authors chose models with unrealistically differential prevalences leading to large effects [11,12] .…”

Section: Introductionmentioning

confidence: 99%

SNP-Based Analysis of Genetic Substructure in the German Population

Steffens

Lamina²,

Illig³

et al. 2006

Hum Hered

122

105

View full text Add to dashboard Cite

Objective: To evaluate the relevance and necessity to account for the effects of population substructure on association studies under a case-control design in central Europe, we analysed three samples drawn from different geographic areas of Germany. Two of the three samples, POPGEN (n = 720) and SHIP (n = 709), are from north and north-east Germany, respectively, and one sample, KORA (n = 730), is from southern Germany. Methods: Population genetic differentiation was measured by classical F-statistics for different marker sets, either consisting of genome-wide selected coding SNPs located in functional genes, or consisting of selectively neutral SNPs from ‘genomic deserts’. Quantitative estimates of the degree of stratification were performed comparing the genomic control approach [Devlin B, Roeder K: Biometrics 1999;55:997–1004], structured association [Pritchard JK, Stephens M, Donnelly P: Genetics 2000;155:945–959] and sophisticated methods like random forests [Breiman L: Machine Learning 2001;45:5–32]. Results: F-statistics showed that there exists a low genetic differentiation between the samples along a north-south gradient within Germany (F_ST(KORA/POPGEN): 1.7 · 10^–4; F_ST(KORA/SHIP): 5.4 · 10^–4; F_ST(POPGEN/SHIP): –1.3 · 10^–5). Conclusion: Although the F_ST-values are very small, indicating a minor degree of population structure, and are too low to be detectable from methods without using prior information of subpopulation membership, such as STRUCTURE [Pritchard JK, Stephens M, Donnelly P: Genetics 2000;155:945–959], they may be a possible source for confounding due to population stratification.

show abstract

Section: Introductionmentioning

confidence: 99%

SNP-Based Analysis of Genetic Substructure in the German Population

Steffens

Lamina²,

Illig³

et al. 2006

Hum Hered

122

105

View full text Add to dashboard Cite

show abstract

“…Here, haplotypes were reconstructed using a maximum likelihood method, and the most likely pair of haplotypes for each individual was used for the analysis. For further discussion about the influence of the uncertainty of haplotype reconstruction, see Jorgenson et al [2005]. In contrast to Beckmann et al [2005a], Humphreys and Iles [2005] found statistical interaction between two genes only for singlelocus approaches, and not for multilocus genotype-or haplotype-based approaches.…”

Section: Haplotype Vs Genotype Approaches To Association Analysismentioning

confidence: 92%

Haplotypes and haplotype-tagging single-nucleotide polymorphism: Presentation Group 8 of Genetic Analysis Workshop 14

Beckmann¹,

Ziegler²,

Duggal³

et al. 2005

Genet. Epidemiol.

View full text Add to dashboard Cite

Moderately dense maps of single-nucleotide polymorphism (SNP) markers across the human genome for both the simulated data set and data from the Collaborative Study of the Genetics of Alcoholism were available at Genetic Analysis Workshop 14 for the first time. This allowed examination of various novel and existing methods for haplotype analyses. Three contributors applied Mantel statistics in different ways for both linkage and association analysis by using the shared length between two haplotypes at a marker locus as a measure of genetic similarity. The results indicate that haplotype-sharing based on Mantel statistics can be a powerful approach and needs further methodological evaluation. Four contributors investigated haplotype-tagging SNP (htSNP) selection procedures, two contributors examined the use of multilocus haplotypes compared to single loci in association tests, and two contributors compared the accuracy of various methods for reconstructing haplotypes and estimating haplotype frequencies for both pedigree data and data from unrelated individuals. For all three different tasks, software packages and procedures gave similar results in regions of high linkage disequilibrium (LD). However, they were not as consistent in regions of moderate to low LD. One coalescence-based approach for estimating haplotype frequencies, coupled with a Markov chain Monte Carlo technique, outperformed the other haplotype frequency estimation methods in regions of low LD. In conclusion, regardless of the task, results were similar in chromosomal regions of high LD. However, based on the differing results observed here, methodological improvements are required for chromosomal regions of low to moderate LD.

show abstract

“…Computations that weigh haplotype probabilities, rather than rely on the single most probable haplotype, become more important as SNP numbers increase. (See also the summary papers by Jorgenson et al [2005] and Beckman et al [2005] for further discussion of this point. )…”

Section: Additional Implications Of Ld and Other Marker Characteristicsmentioning

confidence: 93%

Assessment and implications of linkage disequilibrium in genome-wide single-nucleotide polymorphism and microsatellite panels

Goode

Jarvik

2005

Genet. Epidemiol.

View full text Add to dashboard Cite

Linkage disequilibrium (LD) between markers is more likely to exist in dense genome-wide single-nucleotide polymorphism (SNP) panels than in microsatellite panels. As part of Genetic Analysis Workshop 14 (GAW14), the extent of LD in the Illumina linkage panel III and the Affymetrix Genechip 10 K mapping array was assessed, using data from the Collaborative Study on the Genetics of Alcoholism (COGA). The impact of LD on linkage results was examined in COGA and simulated data, and characteristics of SNPs were assessed for their ability to detect population substructure and predict haplotypes. The authors of the papers summarized here observed greater LD in the Affymetrix than in the Illumina panel, possibly due to increased marker density in the Affymetrix panel, and found greater LD on chromosome X than on the autosomes. Simulation analyses suggest that intermarker LD can cause an upward bias in linkage statistics; however, the impact of LD on linkage analysis depends on the proportion of ungenotyped founders and the extent of LD. No large effect of LD on linkage peaks was observed in COGA analyses. In addition, the papers summarized here found that SNPs with high minor allele frequencies were the most informative compared with microsatellites for the detection of population substructure, and that SNPs in higher LD, and small numbers of SNPs, were the most reliable for haplotype prediction. As ease of genotyping continues to increase, study design and SNP selection for linkage and association studies (including genome-wide association studies) will be improved with consideration of LD in the particular populations studied.

show abstract

Case-control analyses: Geneopardy!

Cited by 4 publications

References 14 publications

SNP-Based Analysis of Genetic Substructure in the German Population

SNP-Based Analysis of Genetic Substructure in the German Population

Haplotypes and haplotype-tagging single-nucleotide polymorphism: Presentation Group 8 of Genetic Analysis Workshop 14

Assessment and implications of linkage disequilibrium in genome-wide single-nucleotide polymorphism and microsatellite panels

Contact Info

Product

Resources

About