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Microarray suite software

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Microarray Suite software is a bioinformatics platform designed to analyze and interpret data generated from microarray experiments. The software provides tools for data processing, statistical analysis, and visualization to support researchers in their gene expression studies.

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10 protocols using microarray suite software

1

Gene Expression Microarray Analysis

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GeneChip Human Gene 1.0 ST Array from Affymetrix was used for expression microarray analysis according to the manufacturer’s protocol. Data were analyzed using Affymetrix Microarray Suite software. All microarray data are available in the GEO database with the accession numbers, GSE132742 and GSE132743. Pathway analysis was carried out using GSEA (http://software.broadinstitute.org/gsea) with hallmark gene sets and GO analysis with biological processes GO terms (https://david.ncifcrf.gov/).
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2

Microarray-based Gene Expression Profiling of Aging Brain

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Gene expression profiling using microarrays has been described previously35 (link). Human brain samples with tissue pH<6.5 or postmortem interval (PMI) >20 hrs were excluded. Prefrontal cortical samples with acceptable parameters of RNA quality were hybridized to Affymetrix Human Genome U133plus 2.0 arrays, which were then scanned and expression data extracted using Affymetrix Microarray Suite Software. The Probe-level Linear Model (PLM) platform was used for analysis of microarray data36 (link). A subset of the data was additionally analyzed using RMA or dCHIP platforms yielding similar results. Significance Analysis of Microarrays (SAM) software37 (link) was used for 2-group comparisons of young adult versus aged with the following criteria for identifying age-related expression changes: 1000 permutations and median false discovery rate (FDR) ≤0.01. Age-regulated genes that overlap with RE1-containing genes38 (link) were visualized by hierarchical clustering using dChip software39 (link) (Fig. 1a). The display range used was 1.5 (a value greater than 1.5 standard deviations above the mean is pure red, below is pure blue, and equal to the mean is white.
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3

Microarray-based Gene Expression Profiling of Aging Brain

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Gene expression profiling using microarrays has been described previously35 (link). Human brain samples with tissue pH<6.5 or postmortem interval (PMI) >20 hrs were excluded. Prefrontal cortical samples with acceptable parameters of RNA quality were hybridized to Affymetrix Human Genome U133plus 2.0 arrays, which were then scanned and expression data extracted using Affymetrix Microarray Suite Software. The Probe-level Linear Model (PLM) platform was used for analysis of microarray data36 (link). A subset of the data was additionally analyzed using RMA or dCHIP platforms yielding similar results. Significance Analysis of Microarrays (SAM) software37 (link) was used for 2-group comparisons of young adult versus aged with the following criteria for identifying age-related expression changes: 1000 permutations and median false discovery rate (FDR) ≤0.01. Age-regulated genes that overlap with RE1-containing genes38 (link) were visualized by hierarchical clustering using dChip software39 (link) (Fig. 1a). The display range used was 1.5 (a value greater than 1.5 standard deviations above the mean is pure red, below is pure blue, and equal to the mean is white.
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4

Affymetrix Microarray Analysis of IMP2-2 Transgenic Mice

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For Affymetrix gene expression microarray analysis RNA was extracted from snap frozen liver tissue of 5 week-old IMP2-2 tg mice (n = 10) and corresponding controls (n = 10), as described in Godoy et al. (32 (link)). The Gene Chip IVT Labeling kit (Affymetrix, High Wycombe, UK) was used to generate biotinylated cRNA. Purification and fragmentation was performed according to Affymetrix's protocol. Hybridization to Mouse Genome 430 2.0 Affymetrix GeneChips (Santa Clara, CA, USA) was conducted for 16 h at 45°C according to the manufacturer's instructions. Microarrays were scanned with an Affymetrix scanner controlled by Affymetrix Microarray Suite software. Robust Multi-array Average (RMA) algorithm (33 (link)) was used for normalization of the gene expression array data and the R package limma (34 (link)) was used for calculation of differential gene expression. Adjustment for multiple testing was conducted with the method of Benjamini and Hochberg (FDR: false discovery rate) (35 (link)). Data are available on Gene Omnibus (GEO-ID: GSE130999).
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5

Gene Expression Microarray Analysis

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For expression microarrays, a GeneChip Human Exon 1.0 ST Array (Affymetrix, Santa Clara, CA, USA) was used according to the manufacturer's protocol as described.9, 10 Data analysis was undertaken using the Affymetrix Microarray Suite software (Santa Clara, CA). To compare arrays, normalization was performed on data from all probe sets. GO term and Pathway analysis was carried out using DAVID.17 These data are available in the Gene Expression Omnibus database (GSE92355).
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6

Microarray Analysis with DAVID

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Expression microarray analysis was performed using the platform of GeneChip Human Gene 1.0 ST Array (Affymetrix) according to the manufacturer’s protocol. Data were analyzed using Affymetrix Microarray Suite software. Pathway analysis was carried out based on the web-accessible program the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources v6.8 (https://david.ncifcrf.gov/).
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7

Adipocyte Gene Expression Profiling

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Adipocytes were isolated from parametrial and periovarian adipose tissues of the mice as described in [29 (link)], and total RNA was extracted from the adipocytes using TRIzol (Life Technologies Corporation) according to manufacturer’s instructions. cDNA was synthesized from the total RNA (two step protocol) and used to prepare biotinylated cRNA for subsequent genome-wide gene expression profiling using Affymetrix MG430-2.0 GeneChips™. Microarray data were obtained from adipocytes from 45 mice under different diet conditions and disease-progression time points: DW8 (n = 5), DW16 (n = 9), DC8 (n = 7), DC16 (n = 5), EW8 (n = 6), EW16 (n = 8) and EC16 (n = 5). Each microarray chip covered ~ 45,000 mouse gene transcripts. The raw intensity values of hybridization were scanned and stored as .CEL files using Affymetrix Microarray suite software with global scaling option. Gene expression values were then obtained by reading and normalizing the .CEL files using Robust Multi Average (RMA) express software. The microarray data sets (one from each mouse) have been uploaded to the GEO database (accession number GSE76428).
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8

Transcriptional Profiling of OCT4 and NRF1 in Prostate Cancer

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To characterize the transcriptional program regulated by OCT4 and NRF1, we performed microarray analysis of PC cells (LNCaP, 22Rv1, DU145-CR, parental DU145, and PC3-CR after 72 h of being transfected with siControl, and two siRNAs targeting OCT4 or NRF1. RNA samples were validated to be high quality (RNA integrity score >9.0) by using RNA bioanalyzer (Agilent, Waldbronn, Germany). For gene expression microarrays, the GeneChip Human Clariom S Array (Affymetrix, Santa Clara, CA) was used in accordance with the manufacturer’s protocol. Data analysis was performed using the Affymetrix Microarray Suite software. To compare arrays, normalization was performed on data from all the probe sets. Kyoto Encyclpedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID 6.7, http://david.ncifcrf.gov/).
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9

Exon Array Analysis of Gene Expression

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For expression microarrays, the GeneChip Human Exon 1.0 ST Array (Affymetrix, Santa Clara, CA) was used according to the manufacturer's protocol. Data analysis was performed using the Affymetrix Microarray Suite software. To compare arrays, normalization was performed on data from all probe sets. For cluster analysis, we used Cluster 3 (downloaded from Eisen laboratory). The data have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO series accession number GSE62454.
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10

Microarray Analysis of Transcriptome

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RNA samples were validated to be high quality (RNA integrity score > 9.0) by using RNA bioanalyzer (Agilent). For gene expression microarrays, the Human Affymetrix Human Gene 1.0 ST Array (Affymetrix) was used in accordance with the manufacturer's protocol. Data analysis was performed using the Affymetrix Microarray Suite software.
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