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Transcriptome profiling of THP-1 cells treated with chemicals

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NIAID Data Ecosystem2026-03-13 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE190511
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We profiled the transcriptome of Dexamethasone-, Tofacitinib-, Tacrolimus-, Prednisolone-, sodium lauryl sulfate (SLS)-, Aciclovir-, Benzoic acid-, Genistein-, Ribavirin-, Mercuric chloride-, Cyclosporine- and LPS-treated monocytes and without chemical-treated (basal, vehicle) monocytes. A Bioconductor software package in R called edgeR was used to conduct the differential expression analysis. Lowly expressed genes were filtered out by keeping only genes with worthwhile counts in a minimum number of samples. The default normalization method in edgeR, trimmed mean of M-values (TMM) normalization was performed, and dispersion estimates (common and tagwise dispersions) were obtained to proceed with differential expression determination. Differentially expressed genes were determined by conducting pairwise comparisons between each type of immunosuppressor or non-immunosuppressor and vehicle or control by applying fold-change and p-value cutoffs (|fold-change| > 1.5 and p-value < 0.05). Each immunosuppressor, excluding sodium lauryl sulfate, was compared with the vehicle group. Immunosuppressor sodium lauryl sulfate and non-immunosuppressor lipopolysaccharide were compared with the basal group. Non-immunosuppressors genistein and ribavirin were compared with the vehicle group. Total RNA profiles of THP-1 cells were used for the differential expression analysis, hierarchical clustering, and gene ontology analysis using the Bioconductor software package in R (edgeR), MeV software, and DAVID bioinformatics resources 6.8.
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2021-12-13
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