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Humanomniexpress beadchip

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The HumanOmniExpress BeadChip is a high-density genotyping microarray designed for comprehensive genome-wide coverage. It is capable of interrogating over 700,000 genetic markers across the human genome.

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Lab products found in correlation

Human610 quad beadchip, by Illumina (16 mentions) Genomestudio software, by Illumina (10 mentions) Genomestudio, by Illumina (6 mentions) Humanexome beadchip, by Illumina (6 mentions) Iscan system, by Illumina (5 mentions) Oragene dna collection kit, by DNA Genotek (4 mentions) Qiaamp dna blood maxi kit, by Qiagen (4 mentions) Humanomni1 quad beadchip, by Illumina (4 mentions) Humanomni 2.5m beadchip, by Illumina (3 mentions) Genomestudio data analysis software, by Illumina (3 mentions) Nanodrop nd 1000 spectrophotometer, by Thermo Fisher Scientific (3 mentions) Vacuette edta tubes, by Greiner (3 mentions) Oragene kit, by DNA Genotek (3 mentions) Infinium human610 quad bead chip, by Illumina (2 mentions) Humanomniexpressexome beadchip, by Illumina (2 mentions) Cytoscan hd array, by Thermo Fisher Scientific (2 mentions) Cnv370 quad chip, by Illumina (2 mentions) Infinium global screening array v2, by Illumina (2 mentions) Nanodrop 8000, by Thermo Fisher Scientific (2 mentions) Omni 2.5m beadchip, by Illumina (2 mentions)

Close spelling variants of this product

HumanOmniExpress (97 citations) BeadChips (68 citations) HumanOmniExpress-24 BeadChip (16 citations) HumanOmniExpress‐12 BeadChip (8 citations) HumanOmniExpress BeadChip Kit (8 citations) HumanOmniExpress-12v1 BeadChip (7 citations) HumanOmniExpress-12v1.0 BeadChip (6 citations) HumanOmniExpress BeadChip array (6 citations) HumanOmniExpress-12v1_H BeadChip (3 citations) HumanOmniExpress Genotyping BeadChip (3 citations)

148 protocols using humanomniexpress beadchip

1

Genotyping Protocols for Genetic Associations

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DNA samples of the Russian cohorts were majorly genotyped using micro-array analysis, as described previously (Pickering et al. 2019 (link)). In part, some DNA samples of Russian athletes and controls were genotyped for the HFE rs1799945 polymorphism with a TaqMan® SNP Genotyping Assay (Thermo Fisher Scientific Inc, Waltham, Massachusetts, USA) with a StepOne TM Real-Time PCR System (Thermo Fisher Scientific Inc, Waltham, Massachusetts, USA) or using PCR-restriction fragment length polymorphism (RFLP) method, according to a previously described method (Merryweather-Clarke et al. 1997 (link)).
Japanese cohort: total DNA was extracted from saliva or venous blood using Oragene DNA Collection Kit (DNA genotek, Ontario, Canada) or QIAamp DNA blood Maxi Kit (QIAGEN, Hilden, Germany), respectively. Illumina® HumanOmniExpress Beadchip (Illumina Inc, Hayward, California, USA) were used for genotyping of more than 700,000 SNPs in athletes and controls. The genotype calls were performed with Illumina® GenomeStudio Software. Genotype data of the HFE rs1799945 polymorphism were obtained from the genotyping results of the Illumina® HumanOmniExpress Beadchip.
Semenova E.A., Miyamoto-Mikami E., Akimov E.B., Al-Khelaifi F., Murakami H., Zempo H., Kostryukova E.S., Kulemin N.A., Larin A.K., Borisov O.V., Miyachi M., Popov D.V., Boulygina E.A., Takaragawa M., Kumagai H., Naito H., Pushkarev V.P., Dyatlov D.A., Lekontsev E.V., Pushkareva Y.E., Andryushchenko L.B., Elrayess M.A., Generozov E.V., Fuku N, & Ahmetov I.I. (2020). The association of HFE gene H63D polymorphism with endurance athlete status and aerobic capacity: novel findings and a meta-analysis. European Journal of Applied Physiology, 120(3), 665-673.
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2

Accounting for Population Structure in Genetic Studies

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Continental ancestry may differ in individuals with the same mtDNA haplogroup, [26 (link)] and self-reported race can be an imperfect proxy for genomically-determined continental ancestry. [27 (link)] To address this potential confounding by population structure we obtained principal component data on a subset of donor-recipient in our study. In the DISCOVeRY-BMT study [28 (link)-31 (link)] 2,167 donor-recipient pairs were genotyped using the Illumina Human OmniExpress BeadChip and the Illumina HumanExome BeadChip. Principal components (PCs) were constructed using a set of independent SNPs across the Illumina Human OmniExpress BeadChip and the first six PCs were used as covariates in place of self-reported race in sensitivity analyses described below.
Spector L.G., Spellman S.R., Thyagarajan B., Beckman K.B., Hoffmann C., Garbe J., Hahn T., Sucheston-Campbell L., Richardson M., De For T.E., Tolar J, & Verneris M.R. (2021). Neither Donor nor Recipient Mitochondrial Haplotypes Are Associated with Unrelated Donor Transplant Outcomes: A Validation Study from the CIBMTR. Transplantation and cellular therapy, 27(10), 836.e1-836.e7.
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3

Large-Scale Genotyping of Asian Cohorts

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Genotyping of 3,072 and 1,952 samples in SiMES and SCES, respectively, was performed using Illumina Human610-Quad BeadChips (Illumina Inc.). A total of 620,901 SNPs were genotyped in each cohort. An additional 635 samples in SCES was genotyped using Illumina Human OmniExpress BeadChips with a total of 729,698 SNPs. Detailed quality control procedures for sample and SNPs were described elsewhere [20] (link), [21] (link). In brief, samples were excluded based on the following conditions: (1) sample call-rates of less than 95%; (2) excessive heterozygosity; (3) cryptic relatedness; (4) gender discrepancies; and (5) discordant ethnic memberships. We excluded SNPs with (1) high missingness (>5%); (2) gross departure from HWE (p value <10−6) and (3) MAF <1%. Detailed quality control procedures for SCES samples genotyped on OmniExpress chips were provided in the supplementary materials (Text S2). After quality control, we have the following samples and SNPs available for analysis: 2,542 samples and 557,824 SNPs in SiMES, 1,889 samples and 538,408 SNPs in SCES on Illumina Human610-Quad BeadChips, and 615 samples and 633,783 SNPs in SCES on Illumina Human OmniExpress BeadChips.
Liao J., Li X., Wong T.Y., Wang J.J., Khor C.C., Tai E.S., Aung T., Teo Y.Y, & Cheng C.Y. (2014). Impact of Measurement Error on Testing Genetic Association with Quantitative Traits. PLoS ONE, 9(1), e87044.
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4

Genome-wide SNP Genotyping and Imputation

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SNPs were genotyped using the Illumina HumanOmniExpress BeadChip for REDUCE and CLUE II populations at the Center for Cancer Genomics at Wake Forest University School of Medicine including 730,525 SNPs across the genome. All 3,103 samples in REDUCE (14 samples were excluded due to poor DNA quality) and 1,136 samples in CLUE II were genotyped. Subjects were removed from subsequent analyses if they met any of the following criteria: (1) overall genotype call rate <90%; (2) duplicates or familial relationship (PI_HAT>0.025). SNPs were excluded if they had: (1) overall genotype call <95%; (2) minor allele frequency (MAF): <0.05 for CLUE II and <0.01 for REDUCE; or (3) P<1×10−3 from a Hardy-Weinberg Equilibrium (HWE) test among controls. Genotypes of SNPs that were not genotyped were imputed by IMPUTE 2.2.2 using the combined data of the 1000 Genomes project and HapMap3 data as reference haplotype maps21 (link). A posterior probability of >0.90 was applied to call genotypes during imputation and the same QC procedure for excluding genotyped SNPs was applied to imputed SNPs.
Na R., Helfand B.T., Chen H., Conran C.A., Crawford S.E., Hayward S.W., Tammela T.L., Hoffman-Bolton J., Zheng S.L., Walsh P.C., Schleutker J., Platz E.A., Isaacs W.B, & Xu J. (2017). A genetic variant near GATA3 implicated in inherited susceptibility and etiology of benign prostatic hyperplasia (BPH) and lower urinary tract symptoms (LUTS). The Prostate, 77(11), 1213-1220.
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5

Genome-wide Genotyping of Brain Samples

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Genomic DNA (200 ng) from each individual brain sample (n=40) was genotyped using the Illumina HumanOmniExpress BeadChip (Illumina). All samples were randomised with respect to gender and disease status to avoid batch effects. Illumina Genome Studio was used to call genotypes (using the HumanOmniExpress-12v1_C.egt cluster file) with the default GenCall cutoff of 0.15. Sex was confirmed by checking the reported sex of each individual against that predicted by the genetic data as described previously.35
Murphy T.M., Crawford B., Dempster E.L., Hannon E., Burrage J., Turecki G., Kaminsky Z, & Mill J. (2017). Methylomic profiling of cortex samples from completed suicide cases implicates a role for PSORS1C3 in major depression and suicide. Translational Psychiatry, 7(1), e989-.
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6

Genome-Wide SNP Genotyping on 23andMe

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Samples were collected and genotyped at the consumer genetics company 23andMe, Inc., as described previously20 (link). Briefly, genotyping was performed on genomic DNA extracted from saliva samples. DNA was genotyped on one of two microarray platforms: the Illumina HumanHap550+ BeadChip platform, which includes more than 550,000 SNPs, or the Illumina HumanOmniExpress+ BeadChip which has a base set of 730,000 SNPs augmented with approximately 250,000 SNPs to obtain a superset of the HumanHap550+, as well as a custom set of about 30,000 SNPs.
Campbell C.L., Furlotte N.A., Eriksson N., Hinds D, & Auton A. (2015). Escape from crossover interference increases with maternal age. Nature Communications, 6, 6260.
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7

Genome-wide Genotyping and Quality Control

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Genome-wide genotyping was performed using Illumina GWAS array platforms (Illumina Human610-Quad BeadChip, Illumina HumanOmni Express BeadChip, and Illumina HumanOmni 2.5 M BeadChip) [12 (link), 13 (link)]. APOE genotyping was separately conducted [12 (link)]. Using PLINK 1.9 (www.cog-genomics.org/plink2/) [14 (link)], we then performed standard quality control (QC) procedures for samples and SNPs as described previously [15 ]: (1) for SNP, SNP call rate < 95%, Hardy-Weinberg P-value < 1 × 10− 6, and minor allele frequency (MAF) < 1%; (2) for sample, sex inconsistencies, and sample call rate < 95%. In order to prevent spurious associations due to population stratification, we used multidimensional scaling analysis to select only non-Hispanic participants of European ancestry that clustered with HapMap CEU (Utah residents with Northern and Western European ancestry from the CEPH collection) or TSI (Toscani in Italia) populations [16 (link), 17 (link)]. After QC procedures (Supplementary Fig. 1), because these cohorts used different genotyping platforms, we imputed un-genotyped SNPs separately in each platform using MaCH with the Haplotype Reference Consortium data as a reference panel [18 (link), 19 (link)].
Park Y.H., Pyun J.M., Hodges A., Jang J.W., Bice P.J., Kim S., Saykin A.J, & Nho K. (2021). Dysregulated expression levels of APH1B in peripheral blood are associated with brain atrophy and amyloid-β deposition in Alzheimer’s disease. Alzheimer's Research & Therapy, 13, 183.
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8

Genome-Wide Genotypic Data Processing

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The sequencing data in ADNI-1 and ADNI-GO/2 was downloaded. In ADNI-1, GenomeStudio v2009.1 (Illumina) was used to process the array data. In ADNI-GO/2, loci were genotyped by the Human OmniExpress BeadChip (Illumina, Inc, San Diego, CA). The ADNI-1 and ADNI-GO/2 datasets consisted of 620,901 and 710,618 genotyped variants respectively, both of which included rs7412 and rs429358 used to define the APOEε2/ε3/ε4 isoforms as previously described [39 (link)]. Finally, all tag SNPs were genotyped in ADNI-GO/2. All but four loci (rs2888903, rs565031, rs7480193, and rs7114401) were genotyped in ADNI-1.
Xu W., Tan C.C., Cao X.P, & Tan L. (2020). Association of Alzheimer’s disease risk variants on the PICALM gene with PICALM expression, core biomarkers, and feature neurodegeneration. Aging (Albany NY), 12(21), 21202-21219.
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9

ADNI Genotyping and Imputation Protocol

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Genotyping for ADNI was performed using the Illumina Human610-Quad BeadChip, Illumina HumanOmni Express BeadChip, and Illumina HumanOmni 2.5M BeadChip platforms. APOE genotyping was separately obtained using standard methods to yield the APOE s4 allele defining SNPs (rs429358, rs7412) (36 (link)). As the ADNI used different genotyping platforms, we imputed un-genotyped SNPs separately in each platform using MACH and the HRC (Haplotype Reference Consortium) data as a reference panel. Before the imputation, we performed standard sample and SNP quality control procedures as described previously (37 (link)): (1 (link)) for SNP, SNP call rate < 95%, Hardy-Weinberg test p<1 x 10-6 (link), and minor allele frequency (MAF) < 1%; (2 (link)) for sample, sample gender and identity check, and sample call rate < 95%. Furthermore, to prevent spurious association due to population stratification, we selected only non-Hispanic Caucasian participants using HapMap data and multidimensional scaling (MDS) analysis (www.hapmap.org) (38 (link)). Imputation and quality control procedures were performed as described previously (39 (link)). After the imputation, we imposed an r2 (link) value equal to 0.30 as the threshold to accept the imputed genotypes.
Lee Y., Han S., Kim D., Kim D., Horgousluoglu E., Risacher S.L., Saykin A.J, & Nho K. (2018). Genetic variation affecting exon skipping contributes to brain structural atrophy in Alzheimer’s disease. AMIA Summits on Translational Science Proceedings, 2018, 124-131.
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10

SORL1 SNP Genotyping in ADNI GWAS

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We extracted the SNP genotypes of SORL1 from the PLINK format data of Genome-wide association study (GWAS) in ADNI database. The ADNI applied the Illumina Infinium Human610-Quad Bead Chip (Illumina, Inc., San Diego, CA) including 620,901 SNP and CNV markers to conduct genotyping for GWAS data, with ADNI-2/GO participants using Illumina Human Omni Express Bead Chip [52 ]. The quality control (QC) procedures were performed using PLINK version 1.07 (http://pngu.mgh.harvard.edu/~purcell/plink/), including filters for missingness, heterozygosity, and concordance between genotype-determined and reported sex. The inclusion criteria are as follows: minimum call rates > 90%, minimum minor allele frequencies (MAF) > 0.01 and Hardy-Weinberg equilibrium test p > 0.001.
Yin R.H., Li J., Tan L., Wang H.F., Tan M.S., Yu W.J., Tan C.C., Yu J.T, & Tan L. (2016). Impact of SORL1 genetic variations on MRI markers in non-demented elders. Oncotarget, 7(22), 31689-31698.
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