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Agilent feature extraction software v11

Manufactured by Agilent Technologies
Sourced in Japan, United States

Agilent Feature Extraction software v11.0 is a data analysis tool designed to extract quantitative information from Agilent microarray data. The software applies algorithms to process raw data and generate numerical values representing the abundance of each feature on the microarray.

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4 protocols using agilent feature extraction software v11

1

Transcriptome Analysis via Microarray

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Total RNA was prepared using an RNeasy mini kit (Qiagen). Purified and labeled RNA was hybridized to an Agilent SurePrint G3 Human Gene Expression v3 8 × 60K Microarray (Design ID: 072363, Agilent, Inc., Santa Clara, CA, USA) in accordance with the manufacturer’s instructions. Microarray results were extracted using Agilent Feature Extraction software v11.0 (Agilent Technologies).
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2

Microarray Analysis of Tissue RNA

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Total RNA from the tissue samples was extracted using the TRIzol reagent (Molecular Research Center) 24 h after the final bacterial or sham administration, and quantified using a NanoDrop 2000 (Thermo Scientific, Wilmington, DE, USA). The total RNA was labeled and then hybridized to an Agilent SurePrint G3 Mouse Gene Expression 8 x 60K mRNA microarray chip (Agilent Technologies). All microarray experiments were conducted in Macrogen, Japan (Kyoto, Japan).
Microarray results were extracted using the Agilent Feature Extraction software v11.0 (Agilent Technologies). Hierarchical cluster analysis was performed using complete linkage and Euclidean distance as a measure of similarity. Gene enrichment and functional annotation analysis for the significant probe list was performed using the GO resource (www.geneontology.org/). All data analyses and visualization of differentially expressed genes were conducted using R 3.3.2 (www.r-project.org).
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3

Microarray Data Analysis Pipeline

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The microarray results were extracted using Agilent Feature Extraction software v11.0 (Agilent Technologies, Inc.). Array probes that had Flag A in the samples were filtered out. Selected gProcessedSignal values were transformed logarithmically and normalized by the quantile method. The significant data was determined by the LPE test and fold-change analysis for which the null hypothesis stated that no differences existed among the groups. The false discovery rate (FDR) was analyzed using the p value of the Benjamini-Hochberg algorithm. Hierarchical cluster analysis was performed by complete linkage and Euclidean distance as the measured of similarity for each DEG set. DEGs were analyzed using Gene enrichment and functional annotation based on the Gene Ontology database (www.geneontology.org/). All data analysis and visualization of the differentially expressed genes were performed using R 3.1.2 (www.r-project.org).
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4

Transcriptome Analysis of Gene Expression

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RNA was isolated with Trizol reagent (Invitrogen, CA, USA) and followed by the RNeasy mini kit from Qiagen, MD, USA (catalog no. 74104). The RNA was labeled and hybridized using the Agilent One-Color Microarray-Based Gene Expression Analysis protocol (Agilent Technology, V 6.5, 2010). The results of the microarray were extracted with Agilent Feature Extraction software v11.0 (Agilent Technologies, Palo Alto, USA). We classified the gene function by using the online resource Database for Annotation, Visualization, and Integrated Discovery (DAVID, v6.8, https://david.ncifcrf.gov/), Interferome (http://www.interferome.org) and Reactome (https://reactome.org/) Microarray data was shown in the link below https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE142624.
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