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Identification of candidate causal perturbations from differential gene expression data

Bioconductor version: Release (3.19)

Compare differential gene expression results with those from known cellular perturbations (such as gene knock-down, overexpression or small molecules) derived from the Connectivity Map. Such analyses allow not only to infer the molecular causes of the observed difference in gene expression but also to identify small molecules that could drive or revert specific transcriptomic alterations.

Author: Bernardo P. de Almeida [aut], Nuno Saraiva-Agostinho [aut, cre], Nuno L. Barbosa-Morais [aut, led]

Maintainer: Nuno Saraiva-Agostinho <nunodanielagostinho at>

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biocViews DifferentialExpression, GeneExpression, GeneSetEnrichment, ImmunoOncology, Pathways, RNASeq, Software, Transcriptomics
Version 1.22.0
In Bioconductor since BioC 3.8 (R-3.5) (5.5 years)
License MIT + file LICENSE
Depends R (>= 4.0)
Imports AnnotationDbi, AnnotationHub, binr, cowplot, data.table, dplyr, DT, fastmatch, fgsea, ggplot2, ggrepel, graphics, highcharter, htmltools, httr, limma, methods, parallel, pbapply, purrr, qs, R.utils, readxl, reshape2, rhdf5, rlang, scales, shiny (>= 1.7.0), shinycssloaders, stats, tibble, tools, utils
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