Computational protocol: Microarray Analysis Reveals Distinct Gene Expression Profiles AmongDifferent Tumor Histology, Stage and Disease Outcomes in EndometrialAdenocarcinoma

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Protocol publication

[…] BeadChip data files are analyzed with Illumina's GenomeStudio gene expression module and R-based Bioconductor package to determine gene expression signal levels . Briefly, the raw intensity of Illumina Human HT-12 v3.0 gene expression array was scanned and extracted using BeadScan, with the data corrected by background subtraction in GenomeStudio module. The lumi module in the R-based Bioconductor Package was used to transform the expression intensity into log2 scale . The log2 transformed intensity data were normalized using Quantile normalization function.We used the Limma program in the R-based Bioconductor package to calculate the level of differential expression . Briefly, a linear model was fit to the data (with cell means corresponding to the different conditions and a random effect for array), and the list of differentially expressed genes (DEGs) with Pvalue<0.01 were obtained by performing the following comparisons based on collected patients' characteristics: USC stage (late vs. early), EAC stage (late vs. early), USC prognosis (good vs. poor), and EAC prognosis (good vs. poor).Following single gene-based significance testing, we used the expression value of DEGs (Pvalue<0.01) to cluster the patients for each comparison. Our purpose was to determine whether the identified DEGs for each comparison are able to serve as potential gene signature to classify patients into their corresponding clinicopathologic groups. Hierarchical clustering algorithm based on the average linkage of Pearson Correlation was employed . The DEGs were analyzed for enriched biological process terms using the NCBI DAVID server (http://david.abcc.ncifcrf.gov) with default setting . All calculations were carried out under R statistics computing. […]

Pipeline specifications

Software tools GenomeStudio, lumi, limma, DAVID
Application Gene expression microarray analysis
Organisms Homo sapiens
Diseases Neoplasms, Endometrial Neoplasms