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Genechip human genome u133 plus 2

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The GeneChip Human Genome U133 Plus 2.0 is a gene expression microarray designed to analyze the expression of over 47,000 transcripts and variants from the human genome. It is capable of simultaneously measuring the expression levels of a large number of genes.

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41 protocols using genechip human genome u133 plus 2

1

Transcription Microarray Analysis and Chromatin Modification

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Transcription microarray analysis was performed by a GeneChip Human Genome U133 Plus 2.0 transcription microarray (Affymetrix, Santa Clara, CA) as described previously [25 (link)]. The scanned data were processed using GeneChip operating software (Affymetrix). The signal intensity of each probe was normalized so that the mean of the signal intensities of all the probes on a microarray would be 500. The mean of the signal intensities of all probes for a gene was used as the transcription level of the gene. Genes were classified into expressed (> 125) gene and unexpressed (< 125) gene according to their signal intensities.
The information on H3K27me3 modification in gastric mucosa was obtained from GEO (GSM772969). LADs of Tig3 cells [44 (link)] and PrEC cells [36 (link)] were obtained from UCSC Genome Browser and GEO (GSM2610545), respectively.
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2

Transcriptome Analysis of Bipolar Disorder

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Fifteen patients with BD all diagnosed according to the revised International Criteria and 14 healthy control subjects were enrolled in the study by Xavier et al [8 (link), 10 (link)]. Total RNA was isolated from peripheral blood mononuclear cells and GeneChip® Human Genome U133 Plus 2.0 (Affymetrix, Santa Clara, CA, USA) microarrays were used for hybridization [8 (link)]. According to the specifications in its product description, the GeneChip® Human Genome U133 Plus 2.0 array is a comprehensive whole human genome expression array which covers >47,000 transcripts for expression profiling. The study by Xavier et al was conducted and reported in accordance with the Minimum Information About Microarray Experiment (MIAME) guidelines and both the raw and the processed microarray data were deposited on GEO database with the Series ID GSE17114 [8 (link), 9 , 11 (link), 12 ].
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3

Curated Age-Dependent AML Transcriptome Datasets

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The curation method is summarized in the Supplementary File S3 flowchart and in the Results section. For our analysis we included 34 age-dependent datasets from 32 different studies, 16 included AML and 18 healthy subjects respectively. From the 34 datasets, 32 were produced from Affymetrix GeneChip Human Genome U133 Plus 2.0 (GPL570) and 2 conducted on Affymetrix GeneChip Human Genome U133 Array Set (GPL96 & GPL97) arrays. Table 1 provides detailed information about each dataset, including the number of samples used from each dataset, sample tissue source, as well as the total number of AML patients and healthy subjects. Two studies, GSE1241755 (link) and GSE3764256 (link)–59 (link), were originally conducted on two different Affymetrix array types (GPL570, and GPL96 & GPL97), so each was separated into two subgroups and each subgroup was considered as individual dataset in our analysis, dataset GSE12417: (i) subgroup 1 included 73 BM and 5 PB samples, and (ii) subgroup 2 included 160 BM and 2 PB. For dataset GSE37642: (i) subgroup 1 included 140 BM and (ii) subgroup 2 included 422 BM samples (Table 1).
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4

Bioinformatics Analysis of Melanoma Microarray Data

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The flow diagram of bioinformatics analysis is shown in Figure 1. Microarray data under the accession number of E-MTAB-1862 were extracted from the European Bioinformatics Institute ArrayExpress database (http://www.ebi.ac.uk/arrayexpress), which were sequenced on the platform of A-AFFY-44—Affymetrix GeneChip Human Genome U133 Plus 2.0 (HG-U133_Plus_2). The E-MTAB-1862 dataset included 21 primary melanoma samples (8 females and 13 males, mean Breslow thickness = 6.8) and 11 benign nevus samples (6 females and 5 males) isolated from skin. In addition, the RNASeqV2 and miRNASeq data of cutaneous melanoma were downloaded from TCGA database. This study just reanalyzed the microarray data downloaded from public database and performed bioinformatics analysis. The authors declare that no experiments were performed on humans or animals for this investigation. Thus, ethics approval or consent to participate was not applicable.
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5

Transcriptome Analysis of Acute Myocardial Infarction

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There were a total of 52 samples (31 AMI and 21 controls) available for transcriptome analysis. Blood samples were collected in EDTA tubes within 48-hours of AMI or following recruitment into the study. Nucleated cells were fractionated from 5 mL of heparinized blood. Total RNA was extracted from cell populations using a combination of gDNA Eliminator and RNeasy columns (Qiagen, Valencia, CA) and was assessed for quality and quantification using Agilent bioanalzyer and OD260/OD280 ratio. Biotinylated cRNA was prepared according to the standard Affymetrix protocol from 100ng total RNA. Following fragmentation, 120ug of cRNA was hybridized for 16 hours at 45°C on Affymetrix GeneChip Human Genome U133 Plus 2.0, which includes 54,675 probsets (http://www.affymetrix.com/estore/), with one sample per array. GeneChips were washed and stained in the Affymetrix Fluidics Station 450 and subsequently scanned using the GeneChip Scanner 3000 7G.
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6

Gene Expression Profiling with Affymetrix GeneChip

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Gene-expression profiles were analyzed with the Affymetrix GeneChip Human Genome U133 Plus 2.0. The target preparation, library labeling, hybridization, post-wash, and signal scanning were performed by CapitalBio Biotechnology (Beijing, China).
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7

Differential Gene Expression in PDAC

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130 human PDAC tumor (n=75) and Adj Norm (n=55) mRNA expression profiles generated on the same array (Affymetrix GeneChip Human Genome U133 Plus 2.0) were downloaded from GEO (https://www.ncbi.nlm.nih.gov/geo/) (GSE15471, GSE16515). Adj Norm samples clustering with PDAC tumors, PDAC tumor profiles clustering with subsets of Adj Norm samples and duplicates were discarded (as previously described (26 (link)), for a remainder of n= 74 tissues (n= 50 PDAC tumor and n= 24 Adj Norm). Raw data were processed and normalized in one batch using a GC-content background correction Robust Multi-array Average (RMA) algorithm (GC-RMA), performed in R: A language and environment for statistical computing. Unpaired Student’s t test were generated in GraphPad Prism (GraphPad Software, CA, USA, www.graphpad.com).
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8

Profiling PTH1R Expression in Breast Cancer

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To study the expression of PTH1R in breast cancer tumors, we identified publicly available microarray data sets from the NCBI and GEO data repositories. The following keywords were used to search the data repositories: breast cancer, bone metastasis, human, murine, gene expression profiling by array. Data sets were further filtered to exclude studies that included drug treatments and metastasis to organs other than bone. Thirty data sets were found, of which 10 studies (n = 3 murine and 7 human) fit the required criteria. They included GDS4077, GDS5666, GSE21444, GDS4091, GSE137842, GDS3853, GSE8977, GSE9014, GDS4761, and GSE57947. All data sets were on an Affymetrix GeneChip Human Genome U133 Plus 2.0 or Affymetrix Human Gene 1.1 platform. Data analysis and statistical analysis were conducted using GEO2R (an online data analysis tool used to analyze GEO data sets under the same experimental conditions), and raw data were retrieved from individual data files as bar charts.
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9

Gene Expression Profiling using GeneChip

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Gene expression profiles were examined by use of a high-density oligonucleotide probe array, GeneChip Human Genome U133 Plus 2.0 (Affymetrix, Santa Clara, CA)20 (link). Total RNA was extracted using the RNeasy® kit (Qiagen, Venlo, Netherlands). cRNA preparation and target hybridization were performed according to the Affymetrix GeneChip technical protocol. The DNA chips were scanned using a specially designed confocal scanner (GeneChip Scanner 3000; Affymetrix). Array data analysis was performed with Affymetrix GeneChip operating software (GCOS) version 1.0.
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10

Molecular Profiling of CLL Response

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RNA extracted from primary CLL cells that responded to OSU-2S was used for gene expression profiling (GEP) performed in Microarray Shared Resource (MASR) in the OSU Comprehensive Cancer Center. RNA Nano bioanalyzer was used to assess the integrity of the RNA samples. The labeled, fragmented cRNA samples were hybridized to GeneChip Human Genome U133 plus 2.0 (Affymetrix, GPL570).22 (link) Detailed data analysis is described in statistics section. To identify possible molecular and cellular functions affected by OSU-2S, genes changed by >2 fold (p<0.0005) were selected for function and network analyses using Ingenuity pathway analysis (IPA) (http://www.ingenuity.com).
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