ttgsea

DOI: 10.18129/B9.bioc.ttgsea  

Tokenizing Text of Gene Set Enrichment Analysis

Bioconductor version: Release (3.16)

Functional enrichment analysis methods such as gene set enrichment analysis (GSEA) have been widely used for analyzing gene expression data. GSEA is a powerful method to infer results of gene expression data at a level of gene sets by calculating enrichment scores for predefined sets of genes. GSEA depends on the availability and accuracy of gene sets. There are overlaps between terms of gene sets or categories because multiple terms may exist for a single biological process, and it can thus lead to redundancy within enriched terms. In other words, the sets of related terms are overlapping. Using deep learning, this pakage is aimed to predict enrichment scores for unique tokens or words from text in names of gene sets to resolve this overlapping set issue. Furthermore, we can coin a new term by combining tokens and find its enrichment score by predicting such a combined tokens.

Author: Dongmin Jung [cre, aut]

Maintainer: Dongmin Jung <dmdmjung at gmail.com>

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("ttgsea")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("ttgsea")

 

HTML	R Script	ttgsea
PDF		Reference Manual
Text		NEWS

Details

biocViews	GeneExpression, GeneSetEnrichment, Software
Version	1.6.3
In Bioconductor since	BioC 3.13 (R-4.1) (2 years)
License	Artistic-2.0
Depends	keras
Imports	tm, text2vec, tokenizers, textstem, stopwords, data.table, purrr, DiagrammeR, stats
LinkingTo
Suggests	fgsea, knitr, testthat, reticulate, rmarkdown
SystemRequirements
Enhances
URL
Depends On Me
Imports Me	DeepPINCS, GenProSeq
Suggests Me
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	ttgsea_1.6.3.tar.gz
Windows Binary	ttgsea_1.6.3.zip (64-bit only)
macOS Binary (x86_64)	ttgsea_1.6.3.tgz
macOS Binary (arm64)	ttgsea_1.6.3.tgz
Source Repository	git clone https://git.bioconductor.org/packages/ttgsea
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/ttgsea
Bioc Package Browser	https://code.bioconductor.org/browse/ttgsea/
Package Short Url	https://bioconductor.org/packages/ttgsea/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.16	Source Archive