eegc

DOI: 10.18129/B9.bioc.eegc    

Engineering Evaluation by Gene Categorization (eegc)

Bioconductor version: Release (3.13)

This package has been developed to evaluate cellular engineering processes for direct differentiation of stem cells or conversion (transdifferentiation) of somatic cells to primary cells based on high throughput gene expression data screened either by DNA microarray or RNA sequencing. The package takes gene expression profiles as inputs from three types of samples: (i) somatic or stem cells to be (trans)differentiated (input of the engineering process), (ii) induced cells to be evaluated (output of the engineering process) and (iii) target primary cells (reference for the output). The package performs differential gene expression analysis for each pair-wise sample comparison to identify and evaluate the transcriptional differences among the 3 types of samples (input, output, reference). The ideal goal is to have induced and primary reference cell showing overlapping profiles, both very different from the original cells.

Author: Xiaoyuan Zhou, Guofeng Meng, Christine Nardini, Hongkang Mei

Maintainer: Xiaoyuan Zhou <zhouxiaoyuan at picb.ac.cn>

Installation

To install this package, start R (version "4.1") and enter:

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

BiocManager::install("eegc")

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("eegc")

 

PDF	R Script	Engineering Evaluation by Gene Categorization (eegc)
PDF		Reference Manual

Details

biocViews	DifferentialExpression, GeneExpression, GeneRegulation, GeneSetEnrichment, GeneTarget, ImmunoOncology, Microarray, RNASeq, Sequencing, Software
Version	1.18.0
In Bioconductor since	BioC 3.4 (R-3.3) (5 years)
License	GPL-2
Depends	R (>= 3.4.0)
Imports	R.utils, gplots, sna, wordcloud, igraph, pheatmap, edgeR, DESeq2, clusterProfiler, S4Vectors, ggplot2, org.Hs.eg.db, org.Mm.eg.db, limma, DOSE, AnnotationDbi
LinkingTo
Suggests	knitr
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
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Build Report

Package Archives

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

Source Package	eegc_1.18.0.tar.gz
Windows Binary	eegc_1.18.0.zip
macOS 10.13 (High Sierra)	eegc_1.18.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/eegc
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/eegc
Package Short Url	https://bioconductor.org/packages/eegc/
Package Downloads Report	Download Stats