Snp arrays

Manufactured by Illumina

Sourced in United States

SNP arrays are laboratory equipment designed for the analysis of single nucleotide polymorphisms (SNPs) within the human genome. The core function of SNP arrays is to provide a high-throughput platform for the simultaneous genotyping of thousands of SNP markers across the genome.

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Lab products found in correlation

1m array, by Illumina (2 mentions) Human cytosnp 12 array, by Illumina (2 mentions) Quantisnp70, by BioDiscovery (2 mentions) Nexus copy number version 7, by BioDiscovery (2 mentions) Omniexpress, by Illumina (1 mentions) Global screening array, by Illumina (1 mentions) Beadstudio software, by Illumina (1 mentions) Humancnv610 quad v1, by Illumina (1 mentions) Massarray, by Labcorp (1 mentions) Infinium humanexome beadchip kit, by Illumina (1 mentions)

Close spelling variants of this product

BovineHD SNPs array Golden Gate SNP Genotyping Arrays SNP 6.0 arrays Human CytoSNP850K SNP arrays HumanHap550 SNP arrays ) SNP genotyping arrays Infinium Omni2.5Exome-8 SNP arrays Infinium HumanCode-24 BeadChip SNP arrays HumanHap550K SNP arrays 510S SNP arrays

14 protocols using snp arrays

Imputing Norwegian Genotype Data

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The Norwegian dataset was genotyped using Illumina SNP arrays (either OmniExpress or Global Screening Array). The chip-genotyping quality control and imputation were performed at deCODE genetics, where the same methods used for the Danish sample were applied. The imputation process relied on the same haplotype reference panel as the Danish sample, a panel composed of phased genotypes of 25,215 WGS samples of European ancestry, including 3,336 samples of Norwegian origin.

Skuladottir A.T., Stefansdottir L., Halldorsson G.H., Stefansson O.A., Bjornsdottir A., Jonsson P., Palmadottir V., Thorgeirsson T.E., Walters G.B., Gisladottir R.S., Bjornsdottir G., Jonsdottir G.A., Sulem P., Gudbjartsson D.F., Knowlton K.U., Jones D.A., Ottas A., Pedersen O.B., Didriksen M., Brunak S., Banasik K., Hansen T.F., Erikstrup C., Haavik J., Andreassen O.A., Rye D., Igland J., Ostrowski S.R., Milani L.A., Nadauld L.D., Stefansson H, & Stefansson K. (2024). GWAS meta-analysis reveals key risk loci in essential tremor pathogenesis. Communications Biology, 7, 504.

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Illumina SNP Array Analysis of Tumors

Cited 2 times

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Illumina SNP arrays were used to analyse the DNA samples from 161 tumour samples (74 Illumina HumanCNV610-Quad v1.0, 52 HumanCNV370, 34 HumanOmniExpress-12v1 and 1 HumanCore-12v1). Integragen SA (Evry, France) carried out hybridization, according to the manufacturer’s recommendations. The BeadStudio software (Illumina) was used to normalize raw fluorescent signals and to obtain log R ratio (LRR) and B allele frequency (BAF) values. Asymmetry in BAF signals due to bias between the two dyes used in Illumina assays was corrected using the tQN normalization procedure.39 (link) We used the circular binary segmentation algorithm40 to segment genomic profiles and assign corresponding smoothed values of log R ratio and B allele frequency. The Genome Alteration Print method was used to determine the ploidy of each sample, the level of contamination with normal cells and the allele-specific copy number of each segment41 (link).

Kamoun A., Idbaih A., Dehais C., Elarouci N., Carpentier C., Letouzé E., Colin C., Mokhtari K., Jouvet A., Uro-Coste E., Martin-Duverneuil N., Sanson M., Delattre J.Y., Figarella-Branger D., de Reyniès A, & Ducray F. (2016). Integrated multi-omics analysis of oligodendroglial tumours identifies three subgroups of 1p/19q co-deleted gliomas. Nature Communications, 7, 11263.

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Genome-Wide Association Study of NAFLD and NASH-HCC

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All of the samples were genotyped with SNP arrays provided by Illumina Inc. (San Diego, CA). The genotyping arrays used and numbers of samples are summarized in the S1 Table. After the genotyping samples were subjected to standard quality controls, association analyses were performed for 93,606 SNPs between 844 NAFLD, 58 NASH-HCC, and 7,672 control samples. A detailed description of the quality control processes is available in the S1 Text.

Kawaguchi T., Shima T., Mizuno M., Mitsumoto Y., Umemura A., Kanbara Y., Tanaka S., Sumida Y., Yasui K., Takahashi M., Matsuo K., Itoh Y., Tokushige K., Hashimoto E., Kiyosawa K., Kawaguchi M., Itoh H., Uto H., Komorizono Y., Shirabe K., Takami S., Takamura T., Kawanaka M., Yamada R., Matsuda F, & Okanoue T. (2018). Risk estimation model for nonalcoholic fatty liver disease in the Japanese using multiple genetic markers. PLoS ONE, 13(1), e0185490.

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Genome-Wide Association Study of Barrett's Esophagus and Adenocarcinoma

Cited 3 times

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We obtained genome-wide genotype data for patients with Barrett's oesophagus, individuals with oesophageal adenocarcinoma, and representative controls from four genome-wide association studies in Europe, North America, and Australia:7 (link), 8 (link), 9 (link) the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON) study; and studies from Bonn, Cambridge, and Oxford (appendix pp 5–6, 11). Data from the Bonn study are unpublished; the Oxford study did not contribute data for patients with oesophageal adenocarcinoma. All participants were of European ancestry, and DNA samples extracted from blood or saliva were genotyped on high-density single nucleotide polymorphism (SNP) arrays (Illumina, San Diego, CA, USA).
Patients with Barrett's oesophagus were identified by histopathological diagnosis of intestinal metaplasia, and individuals with oesophageal adenocarcinoma had a histopathological diagnosis of adenocarcinoma. We excluded all other patients. Informed consent was obtained in the four studies from all participants and ethics approval was obtained from the ethics boards of every participating institution.

Gharahkhani P., Fitzgerald R.C., Vaughan T.L., Palles C., Gockel I., Tomlinson I., Buas M.F., May A., Gerges C., Anders M., Becker J., Kreuser N., Noder T., Venerito M., Veits L., Schmidt T., Manner H., Schmidt C., Hess T., Böhmer A.C., Izbicki J.R., Hölscher A.H., Lang H., Lorenz D., Schumacher B., Hackelsberger A., Mayershofer R., Pech O., Vashist Y., Ott K., Vieth M., Weismüller J., Nöthen M.M., Attwood S., Barr H., Chegwidden L., de Caestecker J., Harrison R., Love S.B., MacDonald D., Moayyedi P., Prenen H., Watson R.G., Iyer P.G., Anderson L.A., Bernstein L., Chow W.H., Hardie L.J., Lagergren J., Liu G., Risch H.A., Wu A.H., Ye W., Bird N.C., Shaheen N.J., Gammon M.D., Corley D.A., Caldas C., Moebus S., Knapp M., Peters W.H., Neuhaus H., Rösch T., Ell C., MacGregor S., Pharoah P., Whiteman D.C., Jankowski J, & Schumacher J. (2016). Genome-wide association studies in oesophageal adenocarcinoma and Barrett's oesophagus: a large-scale meta-analysis. The Lancet. Oncology, 17(10), 1363-1373.

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Copy Number Profiling of Tumor Genomes

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Custom Illumina SNP arrays (~760k positions) were produced for 49 patients (tumor + germline DNA) in order to assess copy number alterations. Genotyping, logR Ratio (LRR) and B-allele-fraction (BAF) were corrected and normalized using the Genotyping module from GenomeStudio 2.0 (Illumina) and all positions with cluster separation >0.75 were exported (594k SNPs) for further analysis. The R package ASCAT^{45 (link)} was used for segmentation of the genome but various tumor DNA purities together with high heterogeneity made it difficult to obtain reliable somatic copy number estimates. Therefore, only the raw-segmented BAF data was used to define genomic regions with allelic imbalance. A sample-specific threshold was defined corresponding to a third of the max BAF segmented value (removing outliers). Regions with strong imbalance reflect genomic regions with either a loss of heterozygosity due to a loss allele (copy number loss) or due to an amplification of only one allele (imbalanced copy number gain) in most of the tumor cells.

Taber A., Christensen E., Lamy P., Nordentoft I., Prip F., Lindskrog S.V., Birkenkamp-Demtröder K., Okholm T.L., Knudsen M., Pedersen J.S., Steiniche T., Agerbæk M., Jensen J.B, & Dyrskjøt L. (2020). Molecular correlates of cisplatin-based chemotherapy response in muscle invasive bladder cancer by integrated multi-omics analysis. Nature Communications, 11, 4858.

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Detecting Genomic Aberrations in Cancers

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The number of SV events was estimated by qSV tool as described above (Supplementary Data 4). The number of double strand breaks per Mb in the genome and each chromosome were estimated for each tumour. If one or more chromosomes presented three times more breaks per Mb than expected and if breaks were equally distributed in the genome, they were classified as localized complex. Evidence of clustering of breakpoints was estimated as proposed by Korbel and Campbell^{36 (link)}. Chromosomes with evidence of clustering of breakpoints (P<0.001, Kolmogorov–Smirnov test—goodness of fit test) were reviewed for: (1) evidence of chromothripsis which included oscillation of copy number, random joins and retention of heterozygosity and (2) evidence of BFB which included loss of telomeric region with neighbouring highly amplified region harbouring inversions. A larger cohort of EACs (n = 101) was screened for evidence of chromothripsis using SNP arrays (Illumina), chromothripsis was inferred in cases where one or few chromosomes showed at least 10 switches in copy number states, with retention of heterozygosity.

Nones K., Waddell N., Wayte N., Patch A.M., Bailey P., Newell F., Holmes O., Fink J.L., Quinn M.C., Tang Y.H., Lampe G., Quek K., Loffler K.A., Manning S., Idrisoglu S., Miller D., Xu Q., Waddell N., Wilson P.J., Bruxner T.J., Christ A.N., Harliwong I., Nourse C., Nourbakhsh E., Anderson M., Kazakoff S., Leonard C., Wood S., Simpson P.T., Reid L.E., Krause L., Hussey D.J., Watson D.I., Lord R.V., Nancarrow D., Phillips W.A., Gotley D., Smithers B.M., Whiteman D.C., Hayward N.K., Campbell P.J., Pearson J.V., Grimmond S.M, & Barbour A.P. (2014). Genomic catastrophes frequently arise in esophageal adenocarcinoma and drive tumorigenesis. Nature communications, 5, 5224.

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Validating Genotyping and Familial Relationships

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Illumina SNP arrays were run on some WGS500 samples and other relatives. This was to check the genotyping accuracy of our sequencing pipeline, to refine linkage regions, to confirm familial relationships, and, in two cases, to investigate whether large stretches of homozygosity were likely due to uniparental disomy or unreported consanguinity. We ran 200 ng of DNA on the Illumina Human CytoSNP12 array or on the 1M array (Illumina Inc.), following the manufacturer’s guidelines. Concordance between the CytoSNP12 genotypes and the WGS data is shown in Supplementary Tables 1 and 2, and the dependence on coverage in Supplementary Figure 2. In most cases, array-CGH had already been performed prior to submission of samples, but we also used QuantiSNP⁷⁰ to check for CNVs, as well as Nexus Copy Number version 7 (BioDiscovery, Hawthorn, CA). We used MERLIN⁷¹ in familial studies to identify regions identical-by-descent.

Taylor J.C., Martin H.C., Lise S., Broxholme J., Cazier J.B., Rimmer A., Kanapin A., Lunter G., Fiddy S., Allan C., Aricescu A.R., Attar M., Babbs C., Becq J., Beeson D., Bento C., Bignell P., Blair E., Buckle V.J., Bull K., Cais O., Cario H., Chapel H., Copley R.R., Cornall R., Craft J., Dahan K., Davenport E.E., Dendrou C., Devuyst O., Fenwick A.L., Flint J., Fugger L., Gilbert R.D., Goriely A., Green A., Greger I.H., Grocock R., Gruszczyk A.V., Hastings R., Hatton E., Higgs D., Hill A., Holmes C., Howard M., Hughes L., Humburg P., Johnson D., Karpe F., Kingsbury Z., Kini U., Knight J.C., Krohn J., Lamble S., Langman C., Lonie L., Luck J., McCarthy D., McGowan S.J., McMullin M.F., Miller K.A., Murray L., Németh A.H., Nesbit M.A., Nutt D., Ormondroyd E., Oturai A.B., Pagnamenta A., Patel S.Y., Percy M., Petousi N., Piazza P., Piret S.E., Polanco-Echeverry G., Popitsch N., Powrie F., Pugh C., Quek L., Robbins P.A., Robson K., Russo A., Sahgal N., van Schouwenburg P.A., Schuh A., Silverman E., Simmons A., Sørensen P.S., Sweeney E., Taylor J., Thakker R.V., Tomlinson I., Trebes A., Twigg S.R., Uhlig H.H., Vyas P., Vyse T., Wall S.A., Watkins H., Whyte M.P., Witty L., Wright B., Yau C., Buck D., Humphray S., Ratcliffe P.J., Bell J.I., Wilkie A.O., Bentley D., Donnelly P, & McVean G. (2015). Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Nature genetics, 47(7), 717-726.

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Genome-wide Genotyping of PACG

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Genome-wide genotyping was performed for a total of 1,854 PACG cases and 9,608 controls using Illumina SNP-arrays. A further 1,917 PACG cases and up to 8,943 controls were genotyped using the Sequenom MassArray and Taqman real-time PCR method (Table S2).

Nongpiur M.E., Khor C.C., Jia H., Cornes B.K., Chen L.J., Qiao C., Nair K.S., Cheng C.Y., Xu L., George R., Tan D., Abu-Amero K., Perera S.A., Ozaki M., Mizoguchi T., Kurimoto Y., Low S., Tajudin L.S., Ho C.L., Tham C.C., Soto I., Chew P.T., Wong H.T., Shantha B., Kuroda M., Osman E.A., Tang G., Fan S., Meng H., Wang H., Feng B., Yong V.H., Ting S.M., Li Y., Wang Y.X., Li Z., Lavanya R., Wu R.Y., Zheng Y.F., Su D.H., Loon S.C., Allingham R.R., Hauser M.A., Soumittra N., Ramprasad V.L., Waseem N., Yaakub A., Chia K.S., Kumaramanickavel G., Wong T.T., How A.C., Chau T.N., Simmons C.P., Bei J.X., Zeng Y.X., Bhattacharya S.S., Zhang M., Tan D.T., Teo Y.Y., Al-Obeidan S.A., Hon D.N., Tai E.S., Saw S.M., Foster P.J., Vijaya L., Jonas J.B., Wong T.Y., John S.W., Pang C.P., Vithana E.N., Wang N, & Aung T. (2014). ABCC5, a Gene That Influences the Anterior Chamber Depth, Is Associated with Primary Angle Closure Glaucoma. PLoS Genetics, 10(3), e1004089.

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Exome Chip Genotyping and Imputation

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The studies employed SNP arrays available from Illumina or Affymetrix. Using available imputation techniques, each cohort imputed approximately > 37 million variants from 1000 Genomes reference panel (phase 1 version 3) and applied strict quality control checks. Further information on the genotyping and imputation methods is detailed in Supplementary Material, Table S3.Exonic and non-exonic variants were genotyped using the Illumina Infinium HumanExome BeadChip kit. The array covers > 240 000 markers, mostly coding variants discovered through exome sequencing in approximately 12 000 individuals and observed at least three times across at least two existing sequence datasets, and includes nonsynonymous, splicing, stop-altering variants, most of which are rare (http://genome.sph.umich.edu/wiki/Exome_Chip_Design). In order to ensure the accurate identification of variants and to minimize population stratification, exome array data quality control was performed based on Best Practices and Joint Calling of the HumanExome BeadChip: The CHARGE Consortium (61 (link)). Further details on methods employed by each study are outlined in supplementary information.

Portilla-Fernandez E., Klarin D., Hwang S.J., Biggs M.L., Bis J.C., Weiss S., Rospleszcz S., Natarajan P., Hoffmann U., Rogers I.S., Truong Q.A., Völker U., Dörr M., Bülow R., Criqui M.H., Allison M., Ganesh S.K., Yao J., Waldenberger M., Bamberg F., Rice K.M., Essers J., Kapteijn D.M., van der Laan S.W., de Knegt R.J., Ghanbari M., Felix J.F., Ikram M.A., Kavousi M., Uitterlinden A.G., Roks A.J., Danser A.H., Tsao P.S., Damrauer S.M., Guo X., Rotter J.I., Psaty B.M., Kathiresan S., Völzke H., Peters A., Johnson C., Strauch K., Meitinger T., O’Donnell C.J, & Dehghan A. (2022). Genetic and clinical determinants of abdominal aortic diameter: genome-wide association studies, exome array data and Mendelian randomization study. Human Molecular Genetics, 31(20), 3566-3579.

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Estimating Tumor Purity and Subclonality

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The ascatNGS algorithm (27 (link)) (v4.0.1) was used to estimate tumor purity and ploidy and to construct copy number profiles before running the Battenberg algorithm (v2.2.5) (github.com/cancerit/cgpBattenberg) to allow for tumor subclonality in bulk DNA sequencing data. For DNA data measured with Illumina SNP arrays, copy number segments were defined by manual inspection of logR and B allele frequency data.

Kildisiute G., Kholosy W.M., Young M.D., Roberts K., Elmentaite R., van Hooff S.R., Pacyna C.N., Khabirova E., Piapi A., Thevanesan C., Bugallo-Blanco E., Burke C., Mamanova L., Keller K.M., Langenberg-Ververgaert K.P., Lijnzaad P., Margaritis T., Holstege F.C., Tas M.L., Wijnen M.H., van Noesel M.M., del Valle I., Barone G., van der Linden R., Duncan C., Anderson J., Achermann J.C., Haniffa M., Teichmann S.A., Rampling D., Sebire N.J., He X., de Krijger R.R., Barker R.A., Meyer K.B., Bayraktar O., Straathof K., Molenaar J.J, & Behjati S. (2021). Tumor to normal single-cell mRNA comparisons reveal a pan-neuroblastoma cancer cell. Science Advances, 7(6), eabd3311.

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