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Genechip snp array 6

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The GeneChip SNP Array 6.0 is a high-density microarray platform designed for the detection and analysis of single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) in the human genome. The array contains over 1.8 million genetic markers, providing comprehensive genome-wide coverage.

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Lab products found in correlation

Uk bileve axiom array, by Thermo Fisher Scientific (1 mentions) Affymetrix genome wide human snp array 6, by Thermo Fisher Scientific (1 mentions) Humancnv370 duo, by Illumina (1 mentions) Infinium humanhap550 chip, by Illumina (1 mentions) 370cnv beadchip system, by Illumina (1 mentions)

Close spelling variants of this product

SNP 6.0 (30 citations) SNP Array 6.0 (27 citations) GeneChips (22 citations) GeneChip arrays (9 citations) GeneChip 6.0 (6 citations) SNP arrays (4 citations) Array 6.0 (2 citations) GeneChip® genome-wide human SNP array 6.0 arrays (2 citations)

4 protocols using genechip snp array 6

1

Genotyping and Imputation of the Pro12Ala Variant

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The Pro12Ala single nucleotide polymorphism in the study participants was genotyped at the Broad Institute (Cambridge, Massachusetts) using the Affymetrix GeneChip SNP Array 6.0® and the Birdseed calling algorithm17 (link). These data were extensively quality-controlled according to accepted standards18 (link), including checks for genetic outliers via average identity-by-state statistics and EIGENSTRAT-generated principal components19 (link). The Pro12Ala (rs1801282) variant was directly measured; we imputed the genotypes for missing values (≤5% of the sample) by exploiting a scaffold containing all variants with ethnic-specific missing rates ≤0.05, minor allele frequencies≥0.01, and Hardy-Weinberg Equilibrium tests >10−5. After pre-phasing with ShapeIt (v1.r532), we employed IMPUTE2 and the 1,000 Genomes haplotypes-Phase I integrated variant set release (v3) reference panel (NCBI Build 37) to impute the missing genotypes20 (link), 21 (link).
West N.A., Tingle J.V., Simino J., Selvin E., Bressler J, & Mosley TH J.r. (2018). The PPARG Pro12Ala Polymorphism and 20-Year Cognitive Decline: Race and Sex Heterogeneity. Alzheimer disease and associated disorders, 32(2), 131-136.
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2

Genotyping and Imputation of UK Biobank and ARIC

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The first 50,000 UK Biobank participants of the full study cohort were genotyped using the Affymetrix UK BiLEVE Axiom array, and the remaining 450,000 participants were genotyped using the Affymetrix UK Biobank Axiom array; the two arrays are more than 95% similar in their variant content. Imputation and initial quality control of UK Biobank SNPs were performed by a collaborative group headed by the Wellcome Trust Centre for Human Genetics. We excluded autosomal SNPs with imputation quality score < 0.5, minor allele frequency (MAF) < 1%, missing genotype per individual > 5%, missing genotype per variant > 2%, or Hardy-Weinberg equilibrium (HWE) P < 1×10−6. After quality control, a total of 7,954,107 autosomal variants among 73,962 participants were included in the analyses. Our quality control and genotype file format conversions were performed using PLINK2 alpha-v2.3 [46 –48 ].
ARIC participants were genotyped using the Affymetrix GeneChip SNP Array 6.0. Before imputation, quality control removed variants with missing rate > 10%, or MAF < 1%, and individuals with missing genotype rate > 80%. After quality control, genotypes were imputed to the ALL ancestry panel of the 1000 Genome Phase III integrate Release Version 5 [49 (link)] using MiniMac software [50 (link)]. After imputation, SNPs with r2 < 0.50, MAF < 1%, or HWE P < 1×10−6 were removed.
Francis M., Li C., Sun Y., Zhou J., Li X., Brenna J.T, & Ye K. (2021). Genome-wide association study of fish oil supplementation on lipid traits in 81,246 individuals reveals new gene-diet interaction loci. PLoS Genetics, 17(3), e1009431.
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3

Genome-Wide Genotyping in Stroke Cohorts

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Genome-wide genotyping in the Framingham Offspring cohort was performed on the AffymetrixGeneChip Human Mapping 500k Array Set and the 50K Human Gene Focused Panel. The genotyping of the KORA sample was performed with the Affymetrix Human Mapping 500k Array 2 chip set (Sty I and NSP I). Genotypes were imputed in both samples to the HapMap CEU panel using MACH algorithm. Genotyping in the GHS I and GHS II was performed using the Affymetrix Genome-Wide Human SNP Array 6.0 (http://www.affymetrix.com), as described by the Affymetrix user manual.
The individual studies included in the stroke population of the CHARGE consortium had finalized their genome-wide association scans before forming the consortium. In the ARIC study, genotyping was performed with the GeneChip SNP Array 6.0 (Affymetrix); in the Cardiovascular Health Study, the HumanCNV370-Duo (Illumina) was used and in the Rotterdam Study, version 3.0 of the Infinium HumanHap550 chip (Illumina) was used.
In the Leeds stroke cohort we used a fluorescence-based assay (Applied Biosystems) to directly genotype the SNPs reaching genome-wide significance in the discovery analysis for SDMA. Genotyping in the HVH study was performed using the Illumina 370CNV BeadChip system.
Filtering and imputation methods are detailed in the Supplemental Information File Section 2.
Lüneburg N., Lieb W., Zeller T., Chen M.H., Maas R., Carter A.M., Xanthakis V., Glazer N.L., Schwedhelm E., Seshadri S., Ikram M.A., Longstreth WT J.r., Fornage M., König I.R., Loley C., Ojeda F.M., Schillert A., Wang T.J., Sticht H., Kittel A., König J., Benjamin E.J., Sullivan L.M., Bernges I., Anderssohn M., Ziegler A., Gieger C., Illig T., Meisinger C., Wichmann H.E., Wild P.S., Schunkert H., Psaty B.M., Wiggins K.L., Heckbert S.R., Smith N., Lackner K., Lunetta K.L., Blankenberg S., Erdmann J., Munzel T., Grant P.J., Vasan R.S, & Böger R.H. (2014). Genome-Wide Association Study of L-Arginine and Dimethylarginines Reveals Novel Metabolic Pathway for Symmetric Dimethylarginine. Circulation. Cardiovascular genetics, 7(6), 864-872.
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4

Genetic Imputation and Quality Control

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Genotyping was independently performed by each cohort using commercially
available arrays ranging from the Illumina 300 and 610 k to the Affymetrix GeneChip SNP
Array 6.0 (Supplementary Table
2). Each cohort applied standard quality control filtering before genetic
imputations. These filters included a SNP call rate of at least 90%, sample call rate of
at least 92%, minor allele frequency of at least 0.01, and Hardy–Weinberg deviation
P-value of at most 10−3 (Supplementary Table 3). Genetic data
imputations were performed in each cohort using HapMap II CEPH (Utah residents with
ancestry from northern and western Europe) as the reference panel, with the exceptions of
ARIC and GENOA African-American cohorts that imputed their genetic data using both HapMap
II CEPH and YRI (Yoruba in Ibadan) populations as a reference.33 (link) Details on genotyping and imputations are provided in Supplementary Tables 2–4.
Ibrahim-Verbaas C., Bressler J., Debette S., Schuur M., Smith A., Bis J., Davies G., Trompet S., Smith J., Wolf C., Chibnik L., Liu Y., Vitart V., Kirin M., Petrovic K., Polasek O., Zgaga L., Fawns-Ritchie C., Hoffmann P., Karjalainen J., Lahti J., Llewellyn D., Schmidt C., Mather K., Chouraki V., Sun Q., Resnick S., Rose L., Oldmeadow C., Stewart M., Smith B., Gudnason V., Yang Q., Mirza S., Jukema J., deJager P., Harris T., Liewald D., Amin N., Coker L., Stegle O., Lopez O., Schmidt R., Teumer A., Ford I., Karbalai N., Becker J., Jonsdottir M., Au R., Fehrmann R., Herms S., Nalls M., Zhao W., Turner S., Yaffe K., Lohman K., van Swieten J., Kardia S., Knopman D., Meeks W., Heiss G., Holliday E., Schofield P., Tanaka T., Stott D., Wang J., Ridker P., Gow A., Pattie A., Starr J., Hocking L., Armstrong N., McLachlan S., Shulman J., Pilling L., Eiriksdottir G., Scott R., Kochan N., Palotie A., Hsieh Y.C., Eriksson J., Penman A., Gottesman R., Oostra B., Yu L., DeStefano A., Beiser A., Garcia M., Rotter J., Nöthen M., Hofman A., Slagboom P., Westendorp R., Buckley B., Wolf P., Uitterlinden A., Psaty B., Grabe H., Bandinelli S., Chasman D., Grodstein F., Räikkönen K., Lambert J.C., Porteous D., Price J., Sachdev P., Ferrucci L., Attia J., Rudan I., Hayward C., Wright A., Wilson J., Cichon S., Franke L., Schmidt H., Ding J., de Craen A., Fornage M., Bennett D., Deary I., Ikram M., Launer L., Fitzpatrick A., Seshadri S., van Duijn C, & Mosley T. (2015). GWAS for executive function and processing speed suggests involvement of the CADM2 gene. Molecular psychiatry, 21(2), 189-197.
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