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Genechip 6

Manufactured by Thermo Fisher Scientific
Sourced in United States

The GeneChip 6.0 is a high-density microarray platform designed for comprehensive genome-wide analysis. It features over 1.8 million probes that cover human, mouse, and rat genomes, enabling researchers to analyze genetic variations and gene expression patterns.

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6 protocols using genechip 6

1

Integrative Proteogenomic Analysis of Dorsolateral Prefrontal Cortex

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We analyzed the proteomes of 400 postmortem brain samples with dorsolateral prefrontal cortex (dPFC) from the ROS/MAP [3 (link)]. In more details, the digested peptides were labeled with isobaric tandem mass tag (TMT) and subjected to liquid chromatography coupled to mass spectrometry (LC–MS) for sequencing. Genotypes were derived from either whole-genome sequencing or genome-wide genotyping by either the Illumina OmniQuad Express or Affymetrix GeneChip 6.0 platforms [15 (link)]. The quality control process was described in the primary study. Finally, 376 subjects with both proteomic and genetic data passed the quality control for the PWAS.
The eQTL dataset was from the PsychENCODE Consortium covering 1,129,652 eQTLs of 11,120 genes from the prefrontal cortex (PFC) (n = 1387) [4 (link)]. We only included the data of SNPs within 1 MB window around each gene. Genotypes were derived either from genome-wide single nucleotide polymorphisms (SNP) arrays or whole genome sequencing.
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2

Genotyping and Imputation of TEDS Cohort

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The Source of DNA for genotyping in the TEDS cohort was saliva collected at the time of recruitment33 (link). The DNA extracted from the saliva was genotyped using either Illumina HumanOmniExpressExome chip or Affymetrix Gene Chip 6.0. Following standard QC procedures, the genotyped markers are phased using EAGLE-255 (link), followed by imputation using MaCH56 (link) with Haplotype reference consortium (release 1.1)57 (link) as the reference panel. Both phasing and imputation were performed through the Sanger imputation services58 (link). Imputation was performed separately for individuals genotyped using Illumina and those genotyped using Affymetrix. The genotyping chip used was accounted for in the genetic analysis by including a dummy variable for the two chips as a covariate.
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3

Multi-omics Profiling of ROS/MAP Cohorts

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The omics data generated on the ROS/MAP cohorts have been described previously. Each data source is presented here and complete details are presented in the supplementary materials.
DNA methylation was measured from the dPFC as previously described in 737 ROS/MAP participant samples (11 (link)), of which 665 had complete phenotype and covariate information. For this study, we re-processed the raw IDAT files, which were downloaded from Synapse (see Web Resources).
Genotyping was generated using two microarrays, Affymetrix GeneChip 6.0 (Affymetrix, Inc, Santa Clara, CA, USA) and Illumina HumanOmniExpress (Illumina, Inc, San Diego, CA, USA), as described previously (20 ).
Gene expression was generated from the dPFC by Illumina HiSeq with 101-bp paired-end reads using the strand-specific dUTP method with poly-A selection with a coverage of 50 million reads. Single-cell RNA-sequencing profiled from the dPFC of 48 individuals from ROS/MAP cohort was performed as described (37 (link)).
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4

Genotyping and Quality Control for GWAS

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ROS/MAP samples were genotyped on the Affymetrix GeneChip 6.0 platform [8 (link)]. We performed sample and SNP quality control procedures on GWAS data (SNP call rate<95%, Hardy-Weinberg equilibrium test p < 10−6 in controls, and frequency filtering MAF<1%) were performed. After the standard quality control procedures for genetic markers and subjects, only non-Hispanic Caucasian participants were selected by clustering with CEU (Utah residents with Northern and Western European ancestry from the CEPH collection) + TSI (Toscani in Italia) populations using HapMap 3 genotype data and the multidimensional scaling (MDS) analysis [9 (link)]. Un-genotyped SNPs were imputed using MaCH and the 1000 Genomes Project as a reference panel [10 (link)]. Final SNP data used for the analysis is coded as the number of minor alleles.
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5

Genetic Variants Associated with Neuroticism

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SNP data were available from the ROSMAP cohort who had completed a range of personality trait questionnaires. Details on GWAS data generation have been described previously43 (link). Briefly, DNA for genotyping was collected from blood, lymphocytes or postmortem brain tissue. The majority of samples (N = 1,709) were genotyped on the Affymetrix GeneChip 6.0 platform and additional samples (N = 384) were genotyped on the Illumina OmniQuad Express platform. Imputation was performed by Alzheimer’s Disease Genetics Consortium on Michigan Imputation Server using the Haplotype Reference Consortium (HRC) reference panel (release 1.1). After quality control, the HRC imputed data were available in 2,182 ROSMAP participants. This dataset was used to identify significant SV2A SNPs associated with neuroticism and anxiety, based on a 10-item anxiety questionnaire (N = 1,706).
PLINK44 (link) was used to test the effects of SNPs with minor allele frequency >1%, including imputed SNPs, to perform set-based tests for all SNPs that mapped to SV2A (±20 kilo-bases). The set-based parameters were r2 = 0.5, p value = 0.05, maximum number of SNPs = 5, and max (T) permutations = 10,000. SV2A SNPs identified by PLINK were also cross-referenced against published summary statistics10 (link) from the meta-analysis and GWAS for neuroticism and worry, with samples ranging from 340,569 to 390,278 individuals.
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6

Integrated Multi-Omics Analysis of Dorsolateral Prefrontal Cortex

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The discovery PWAS data were obtained from the dorsolateral prefrontal cortex (dPFC) of postmortem brain tissues from 376 subjects recruited by the Religious Orders Study/Memory and Aging Project (ROS/MAP) [19 (link)]. For proteome sequencing, isobaric tandem mass tag peptide labeling was utilized, and peptides were assessed using liquid chromatography coupled to mass spectrometry (MS) [20 (link)]. Wingo et al. [21 (link)] used Thermo Fisher Scientific’s Proteome Discoverer suite v.2.3 and tandem MS spectra to search against the standard UniProtKB human proteome database, which has 20,338 total sequences, to assign peptide spectral matches. Genotyping was done using whole-genome sequencing or genome-wide genotyping on the Illumina OmniQuad Express or Affymetrix GeneChip 6.0 platforms. Over 8356 proteins having both proteomic and genomic data, among which 1475 protein could find significant cis associations with genetic variation.
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