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R/Bioconductor package including the Gene Expression Signature Search (GESS), Function Enrichment Analysis (FEA) methods and supporting drug-target network construction for visualization
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README.md

signatureSearch - Environment for Gene Expression Searching Combined with Functional Enrichment Analysis

Introduction

The signatureSearch package implements algorithms and data structures for performing gene expression signature (GES) searches, and subsequently interpreting the results functionally with specialized enrichment methods. These utilities are useful for studying the effects of genetic, chemical and environmental perturbations on biological systems. Specifically, in drug discovery they can be used for identifying novel modes of action (MOA) of bioactive compounds from reference databases such as LINCS containing the genome-wide GESs from tens of thousands of drug and genetic perturbations (Subramanian et al. 2017). A typical GES search (GESS) workflow can be divided into two major steps. First, GESS methods are used to identify perturbagens such as drugs that induce GESs similar to a query GES of interest. The queries can be drug-, disease- or phenotype-related GESs. Since the MOAs of most drugs in the corresponding reference databases are known, the resulting associations are useful to gain insights into pharmacological and/or disease mechanisms, and to develop novel drug repurposing approaches. Second, specialized functional enrichment analysis (FEA) methods using annotations systems, such as Gene Ontologies (GO), pathways or Disease Ontologies (DO), have been developed and implemented in this package to efficiently interpret GESS results. The latter are usually composed of lists of perturbagens (e.g. drugs) ranked by the similarity metric of the corresponding GESS method. Finally, network resconstruction functionalities are integrated for visualizing the final results, e.g. in form of drug-target networks. For each GESS and FEA step, several alternative methods have been implemented in signatureSearch to allow users to choose the best possible workflow configuration for their research application.

Vignette

The vignette of this package is available at here

Installation and Loading

signatureSearch is a R/Bioconductor package and can be installed using BiocManager::install().

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("signatureSearch")

To obtain the most recent updates immediately, one can install it directly from GitHub as follows.

devtools::install_github("yduan004/signatureSearch")

After the package is installed, it can be loaded into an R session as follows.

library(signatureSearch)

For detailed description of the package, please refer to the vignette by running

browseVignettes("signatureSearch")
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