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Axiom biobank genotyping array

Manufactured by Thermo Fisher Scientific
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The Axiom Biobank Genotyping Array is a high-throughput genotyping platform designed for large-scale genomic research and biobanking applications. The array provides comprehensive genome-wide coverage and enables the analysis of genetic variations across diverse populations.

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8 protocols using axiom biobank genotyping array

1

Genotype Imputation and Quality Control

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PGP and HABS subjects were genotyped from whole blood DNA using the Illumina Infinium HumanOmniExpressExome BeadChip Kit (San Diego, CA) and the Affymetrix Axiom Biobank Genotyping Array (Santa Clara, CA), respectively. In short, EIGENSTRAT v3.0 was used to identify population outliers, which were discarded. The BEAGLE software (version: 3.3.2) was used to impute the post-QC genotyped markers using reference Haplotype panels from the 1000 Genomes Project Consortium Phase I Integrated Release Version 3 (for PGP) or Version 1 (for HABS). These methods are described in detail elsewhere12 (link).
In ROS-MAP, DNA was extracted from whole blood or frozen post-mortem brain tissue. Genotype data was generated using the Affymetrix Genechip 6.0 platform at the Broad Institute’s Genetic Analysis Platform or the Translational Genomics Research Institute, as previously described24 (link). In short, data underwent quality control analyses using the PLINK toolkit (http://pngu.mgh.harvard.edu/~purcell/ plink/) and quality controlled genotypes were pooled. The quality control process included a principal components analysis using default parameters in EIGENSTRAT to identify and remove population outliers. Imputation in ROS-MAP was performed using MACH software (version 1.0.16a) and HapMap release 22 CEU (build 36).
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2

Genetic Variants and Kidney Disease

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Samples from the discovery and trait discrimination stages (to discriminate association with nephropathy from association with T2D per se) were genotyped on a custom Affymetrix Axiom Biobank Genotyping Array (Affymetrix, Santa Clara, CA, USA). Detailed SNP information, custom content design, including fine mapping of candidate regions, genotyping methods, and quality control are described in the Supplementary Methods. The final data set consisted of 3848 subjects with relevant phenotypes for analysis. Relevant to this study, 4588 highly dense SNPs flanking 25-kb upstream and downstream of the 47 selected candidate genes which passed standard quality control (QC) were examined in the discovery stage.
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3

Genetic Profiling of Vasculitis Patients

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All included patients had available DNA samples. Affymetrix Axiom Biobank Genotyping Array was used for genotyping 286 patients as part of the Vasculitis Clinical Research Consortium GWAS (2 (link)). An additional 115 patients and 130 healthy controls were genotyped by PCR (including confirmation of 15 of the GWAS patients), via amplification of the SNP-containing region using forward primer 5′ GAGCTGACTCATGGCTGAAACCAAC 3′, reverse primer 5′ TGATGTGTATTAAAGAACTAGAGCT 3′. PCR products were separated by agarose gel electrophoresis and imaged using iBright FL1000 (Invitrogen, Thermo Fisher Scientific) (Supplemental Figure 1).
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4

Genotype Imputation and Quality Control

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PGP and HABS subjects were genotyped from whole blood DNA using the Illumina Infinium HumanOmniExpressExome BeadChip Kit (San Diego, CA) and the Affymetrix Axiom Biobank Genotyping Array (Santa Clara, CA), respectively. In short, EIGENSTRAT v3.0 was used to identify population outliers, which were discarded. The BEAGLE software (version: 3.3.2) was used to impute the post-QC genotyped markers using reference Haplotype panels from the 1000 Genomes Project Consortium Phase I Integrated Release Version 3 (for PGP) or Version 1 (for HABS). These methods are described in detail elsewhere12 (link).
In ROS-MAP, DNA was extracted from whole blood or frozen post-mortem brain tissue. Genotype data was generated using the Affymetrix Genechip 6.0 platform at the Broad Institute’s Genetic Analysis Platform or the Translational Genomics Research Institute, as previously described24 (link). In short, data underwent quality control analyses using the PLINK toolkit (http://pngu.mgh.harvard.edu/~purcell/ plink/) and quality controlled genotypes were pooled. The quality control process included a principal components analysis using default parameters in EIGENSTRAT to identify and remove population outliers. Imputation in ROS-MAP was performed using MACH software (version 1.0.16a) and HapMap release 22 CEU (build 36).
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5

Genome-wide SNP Data Analysis of Peruvian Andean and Mexican Maya

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Genome-wide SNP data were generated using the Affymetrix (Santa Clara, CA) Axiom Biobank Genotyping Array for all Peruvian Andean and Mexican Maya study participants. We performed a PCA using 405,419 variants that were filtered for linkage disequilibrium (r2 > 0.8) and genotyping rate (<0.1) in Plink 2.0 (Purcell et al. 2007 (link); Chang et al. 2015 (link)) (fig. 1). PCA included publicly available data from the 1000 Genomes Project for 60 Yorubans (YRI), 45 CHB, 45 Japanese from Tokyo (JPT), and 60 individuals of north-central European ancestry (CEU) from the Human Genome Diversity Project-Centre d’Etude du Polymorphisme Humain (HGDP-CEPH) (1000 Genomes Project Consortium). Participant relatedness was estimated using KING (Manichaikul et al. 2010 (link)) in PLINK 2.0. Three individuals related at the first-degree level and six individuals related at the second-degree level were identified and excluded from genotype–phenotype association testing. Standard linear regression was performed in PLINK using dominant and additive models of inheritance (Purcell et al. 2007 (link)). Regression coefficients were calculated for the minor allele. Participant sex and the first five PCs were included as covariates in the models.
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6

Genotype-ncRNA Expression Association Analysis

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Genomewide genotyping of the iliac bone donors was performed using the Affymetrix Axiom Biobank Genotyping Array (Affymetrix, Santa Clara, CA, USA) (~700,000 SNPs assessed), (26) followed by imputation to the haplotype reference panel (HRC 1.0). SNPs with minor allele frequency (MAF) > 0.05 and imputation quality (R2) > 0.3 were considered for further analysis. Combining the available genotyped patient data and iliac bone ncRNA expression data of patients yielded data of 77 patients in total. We then used a two-step approach to assess the association of SNPs with the expression of each ncRNA. First, using linear models we adjusted the ncRNA expression for either age or age and BMI, and then defined the model residuals as either age-adjusted RNA expressions or age-and BMI-adjusted RNA expression. These model residuals were scaled using zero mean unit variance standardization. Second, we performed cis-eQTL analyses, using the Rvtests software package with single variant tests, (27) for each adjusted ncRNA expression. SNPs within 500 kilobases (kb) of the ncRNA transcription start or termination sites were surveyed. Values of p of association were adjusted for multiple testing (FDR < 0.05).
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7

Brain Transcriptome and Genotyping Analysis

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RNA was extracted from the brain tissues using the Qiagen RNeasy kit (Qiagen, Germantown, MD). The RNA-seq samples were prepared using the TruSeq RNA Library Pre Kit v2 (Illumina, Inc., San Diego, CA) and sequenced on the Illumina HiSeq 2000. Paired-end libraries with an average insert size of 180 bp were obtained. Raw reads were aligned to human genome 19 (hg19) using STAR aligner version 2.5.3.a [15 (link)]. FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) was used to evaluate RNA sequence quality. The RNA-seq data is available through the NCBI BioProject database (BLA: PRJNA551909, CE: PRJNA551908, NAC: PRJNA551775, SFC: PRJNA530758).
DNA was obtained from the same brain tissues. The Axiom Biobank Genotyping Array (Thermo Fisher Scientific, Waltham, MA) was used for genotyping. Monomorphic variants, variants with call rate ≤ 0.98 or Hardy-Weinberg Equilibrium p < 10−5, and samples with call rate < 0.90 were removed using PLINK [16 (link)]. Phasing was done using SHAPEIT2 [17 (link)]. IMPUTE2 [18 (link)] was used for imputation using the 1,000 Genomes Phase 1 integrated panel (excluding singleton variants) as the reference. Variants with imputation score ≥ 0.8 and estimated minor allele frequency (MAF) ≥ 0.5 were included in the analysis.
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8

Brain Tissue Transcriptome and Genotype Analysis

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RNA was extracted from the brain tissues using the Qiagen RNeasy kit (Qiagen, Germantown, MD, USA). The RNA-seq samples were prepared using the TruSeq RNA Library Pre Kit v2 (Illumina, Inc., San Diego, CA, USA) and sequenced on the Illumina HiSeq 2000. Paired-end libraries with an average insert size of 180 bp were obtained. Raw reads were aligned to human genome 19 (hg19) using STAR aligner version 2.5.3.a [15 (link)]. FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) was used to evaluate RNA sequence quality. The RNA-seq data is available through the NCBI BioProject database (BLA: PRJNA551909, CE: PRJNA551908, NAC: PRJNA551775, SFC: PRJNA530758).
DNA was obtained from the same brain tissues. The Axiom Biobank Genotyping Array (Thermo Fisher Scientific, Waltham, MA, USA) was used for genotyping. Monomorphic variants, variants with call rate ≤0.98 or Hardy–Weinberg equilibrium p < 10−5, and samples with call rate <0.90 were removed using PLINK [16 (link)]. Phasing was done using SHAPEIT2 [17 (link)]. IMPUTE2 [18 (link)] was used for imputation using the 1000 Genomes Phase 1 integrated panel (excluding singleton variants) as the reference. Variants with imputation score ≥0.8 and estimated minor allele frequency (MAF) ≥0.5 were included in the analysis.
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