{
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  "Package": "tRanslatome",
  "Type": "Package",
  "Title": "Comparison between multiple levels of gene expression",
  "Version": "1.51.0",
  "Date": "2023-02-03",
  "Author": "Toma Tebaldi, Erik Dassi, Galena Kostoska",
  "Maintainer": "Toma Tebaldi <toma.tebaldi@unitn.it>, Erik Dassi\n<erik.dassi@unitn.it>",
  "Description": "Detection of differentially expressed genes (DEGs) from\nthe comparison of two biological conditions (treated vs.\nuntreated, diseased vs. normal, mutant vs. wild-type) among\ndifferent levels of gene expression (transcriptome\n,translatome, proteome), using several statistical methods:\nRank Product, Translational Efficiency, t-test, Limma, ANOTA,\nDESeq, edgeR. Possibility to plot the results with\nscatterplots, histograms, MA plots, standard deviation (SD)\nplots, coefficient of variation (CV) plots. Detection of\nsignificantly enriched post-transcriptional regulatory factors\n(RBPs, miRNAs, etc) and Gene Ontology terms in the lists of\nDEGs previously identified for the two expression levels.\nComparison of GO terms enriched only in one of the levels or in\nboth. Calculation of the semantic similarity score between the\nlists of enriched GO terms coming from the two expression\nlevels. Visual examination and comparison of the enriched terms\nwith heatmaps, radar plots and barplots.",
  "License": "GPL-3",
  "LazyLoad": "yes",
  "biocViews": "CellBiology, GeneRegulation, Regulation, GeneExpression,\nDifferentialExpression, Microarray, HighThroughputSequencing,\nQualityControl, GO, MultipleComparisons, Bioinformatics",
  "Packaged": {
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  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:37:44 UTC",
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