Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples

H. Hong; L. Shi; Z. Su; W. Ge; W. D. Jones; W. Czika; K. Miclaus; C. G. Lambert; S. C. Vega; J. Zhang; B. Ning; J. Liu; B. Green; L. Xu; H. Fang; R. Perkins; S. M. Lin; N. Jafari; K. Park; T. Ahn; M. Chierici; C. Furlanello; L. Zhang; R. D. Wolfinger; F. Goodsaid; W. Tong

doi:10.1038/tpj.2010.24

Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples

H. Hong^*, L. Shi, Z. Su, W. Ge, W. D. Jones, W. Czika, K. Miclaus, C. G. Lambert, S. C. Vega, J. Zhang, B. Ning, J. Liu, B. Green, L. Xu, H. Fang, R. Perkins, S. M. Lin, N. Jafari, K. Park, T. AhnM. Chierici, C. Furlanello, L. Zhang, R. D. Wolfinger, F. Goodsaid, W. Tong

^*Corresponding author for this work

Center for Genetic Medicine

Research output: Contribution to journal › Article › peer-review

21 Scopus citations

Abstract

The discordance in results of independent genome-wide association studies (GWAS) indicates the potential for Type I and Type II errors. We assessed the repeatibility of current Affymetrix technologies that support GWAS. Reasonable reproducibility was observed for both raw intensity and the genotypes/copy number variants. We also assessed consistencies between different SNP arrays and between genotype calling algorithms. We observed that the inconsistency in genotypes was generally small at the specimen level. To further examine whether the differences from genotyping and genotype calling are possible sources of variation in GWAS results, an association analysis was applied to compare the associated SNPs. We observed that the inconsistency in genotypes not only propagated to the association analysis, but was amplified in the associated SNPs. Our studies show that inconsistencies between SNP arrays and between genotype calling algorithms are potential sources for the lack of reproducibility in GWAS results.

Original language	English (US)
Pages (from-to)	364-374
Number of pages	11
Journal	Pharmacogenomics Journal
Volume	10
Issue number	4
DOIs	https://doi.org/10.1038/tpj.2010.24
State	Published - Aug 2010

Funding

HH thanks Dr Williams Slikker for his support on this research project. LX thanks NCTR-US FDA for providing the ORISE postdoctoral research fellowship to participate in the project.

Keywords

association
calling algorithm
copy number
genotype
intensity
repeatability

ASJC Scopus subject areas

Molecular Medicine
Genetics
Pharmacology

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10.1038/tpj.2010.24

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Hong, H., Shi, L., Su, Z., Ge, W., Jones, W. D., Czika, W., Miclaus, K., Lambert, C. G., Vega, S. C., Zhang, J., Ning, B., Liu, J., Green, B., Xu, L., Fang, H., Perkins, R., Lin, S. M., Jafari, N., Park, K., ... Tong, W. (2010). Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples. Pharmacogenomics Journal, 10(4), 364-374. https://doi.org/10.1038/tpj.2010.24

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title = "Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples",

abstract = "The discordance in results of independent genome-wide association studies (GWAS) indicates the potential for Type I and Type II errors. We assessed the repeatibility of current Affymetrix technologies that support GWAS. Reasonable reproducibility was observed for both raw intensity and the genotypes/copy number variants. We also assessed consistencies between different SNP arrays and between genotype calling algorithms. We observed that the inconsistency in genotypes was generally small at the specimen level. To further examine whether the differences from genotyping and genotype calling are possible sources of variation in GWAS results, an association analysis was applied to compare the associated SNPs. We observed that the inconsistency in genotypes not only propagated to the association analysis, but was amplified in the associated SNPs. Our studies show that inconsistencies between SNP arrays and between genotype calling algorithms are potential sources for the lack of reproducibility in GWAS results.",

keywords = "association, calling algorithm, copy number, genotype, intensity, repeatability",

author = "H. Hong and L. Shi and Z. Su and W. Ge and Jones, {W. D.} and W. Czika and K. Miclaus and Lambert, {C. G.} and Vega, {S. C.} and J. Zhang and B. Ning and J. Liu and B. Green and L. Xu and H. Fang and R. Perkins and Lin, {S. M.} and N. Jafari and K. Park and T. Ahn and M. Chierici and C. Furlanello and L. Zhang and Wolfinger, {R. D.} and F. Goodsaid and W. Tong",

note = "Funding Information: HH thanks Dr Williams Slikker for his support on this research project. LX thanks NCTR-US FDA for providing the ORISE postdoctoral research fellowship to participate in the project.",

year = "2010",

month = aug,

doi = "10.1038/tpj.2010.24",

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Hong, H, Shi, L, Su, Z, Ge, W, Jones, WD, Czika, W, Miclaus, K, Lambert, CG, Vega, SC, Zhang, J, Ning, B, Liu, J, Green, B, Xu, L, Fang, H, Perkins, R, Lin, SM, Jafari, N, Park, K, Ahn, T, Chierici, M, Furlanello, C, Zhang, L, Wolfinger, RD, Goodsaid, F & Tong, W 2010, 'Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples', Pharmacogenomics Journal, vol. 10, no. 4, pp. 364-374. https://doi.org/10.1038/tpj.2010.24

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T1 - Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples

AU - Hong, H.

AU - Shi, L.

AU - Su, Z.

AU - Ge, W.

AU - Jones, W. D.

AU - Czika, W.

AU - Miclaus, K.

AU - Lambert, C. G.

AU - Vega, S. C.

AU - Zhang, J.

AU - Ning, B.

AU - Liu, J.

AU - Green, B.

AU - Xu, L.

AU - Fang, H.

AU - Perkins, R.

AU - Lin, S. M.

AU - Jafari, N.

AU - Park, K.

AU - Ahn, T.

AU - Chierici, M.

AU - Furlanello, C.

AU - Zhang, L.

AU - Wolfinger, R. D.

AU - Goodsaid, F.

AU - Tong, W.

N1 - Funding Information: HH thanks Dr Williams Slikker for his support on this research project. LX thanks NCTR-US FDA for providing the ORISE postdoctoral research fellowship to participate in the project.

PY - 2010/8

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N2 - The discordance in results of independent genome-wide association studies (GWAS) indicates the potential for Type I and Type II errors. We assessed the repeatibility of current Affymetrix technologies that support GWAS. Reasonable reproducibility was observed for both raw intensity and the genotypes/copy number variants. We also assessed consistencies between different SNP arrays and between genotype calling algorithms. We observed that the inconsistency in genotypes was generally small at the specimen level. To further examine whether the differences from genotyping and genotype calling are possible sources of variation in GWAS results, an association analysis was applied to compare the associated SNPs. We observed that the inconsistency in genotypes not only propagated to the association analysis, but was amplified in the associated SNPs. Our studies show that inconsistencies between SNP arrays and between genotype calling algorithms are potential sources for the lack of reproducibility in GWAS results.

AB - The discordance in results of independent genome-wide association studies (GWAS) indicates the potential for Type I and Type II errors. We assessed the repeatibility of current Affymetrix technologies that support GWAS. Reasonable reproducibility was observed for both raw intensity and the genotypes/copy number variants. We also assessed consistencies between different SNP arrays and between genotype calling algorithms. We observed that the inconsistency in genotypes was generally small at the specimen level. To further examine whether the differences from genotyping and genotype calling are possible sources of variation in GWAS results, an association analysis was applied to compare the associated SNPs. We observed that the inconsistency in genotypes not only propagated to the association analysis, but was amplified in the associated SNPs. Our studies show that inconsistencies between SNP arrays and between genotype calling algorithms are potential sources for the lack of reproducibility in GWAS results.

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Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples

Abstract

Funding

Keywords

ASJC Scopus subject areas

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