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Ht 12 v4.0 beadchips

Manufactured by Illumina

The HT-12 v4.0 BeadChips are a high-throughput gene expression microarray platform designed for genome-wide transcriptional profiling. The BeadChips contain more than 47,000 probes targeting well-characterized genes, gene candidates, and splice variants, allowing for comprehensive analysis of the human transcriptome in a single experiment.

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4 protocols using ht 12 v4.0 beadchips

1

Illumina HT-12 v4.0 BeadChip Gene Expression

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Samples were split randomly over four Illumina HT-12 v4.0 BeadChips to minimise any effect of inter-chip variability. One sample was used per well. The chips were imaged using a BeadArray Reader and raw data were obtained with Illumina BeadStudio software. Raw and processed data are available at www.ebi.ac.uk/arrayexpress/ under accession number E-MTAB-3136.
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2

Illumina HT-12 v4.0 BeadChip Processing

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Samples were randomly split over three Illumina HT-12 v4.0 BeadChips to minimize the effects of inter-chip variability. The chips were imaged using a BeadArray Reader and raw data were obtained with Illumina BeadStudio software. Raw data are available at www.ebi.ac.uk/arrayexpress under accession number E-MTAB-5353.
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3

Illumina Microarray Data Processing

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Microarrays were performed on biological triplicates using Illumina HT12-v4.0 bead chips, and the raw data were processed using Genome Studio (Illumina) and normalized using the R/Bioconductor package lumi. The raw and processed microarray data are available on ArrayExpress (E-MTAB-2749). Microarray bioinformatic analyses are described in the Supplemental Material.
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4

Transcriptome analysis of gene expression

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Total RNA extracted using Trizol reagent (Invitrogen) and verified for integrity and purity, was labeled using Illumina TotalPrep RNA amplification kit (Ambion, Austin, TX) as per manufacturer's instructions. The cRNA generated was hybridized to Illumina HT-12 v4.0 BeadChips at 58°C for 18 h. The BeadChips were then washed, stained, and scanned using iScan (Illumina). Data files were quantified in GenomeStudio v2011.1 (Illumina), quantile normalized using the lumi package of Bioconductor [33] (link), and filtered using varFilter to retain the 10% most variable probes. Data for multiple probes targeting the same gene were collapsed to their median value and annotated with gene names using GenePattern [34] (link). The collapsed data were analyzed using the linear models for microarray analysis (LIMMA) package [35] (link) to identify differentially expressed genes. To understand the relationship among differentially expressed genes further, we performed a network-based analysis using the Reactome Functional Interaction (FI) Network plugin for Cytoscape [36] (link). The gene expression profiling data can be accessed from the NCBI Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo. Accessed 2014 May 1), accession number GSE54608.
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