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eegc

Engineering Evaluation by Gene Categorization (eegc)


Bioconductor version: Release (3.18)

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>

Citation (from within R, enter citation("eegc")):

Installation

To install this package, start R (version "4.3") and enter:


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

BiocManager::install("eegc")

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

Documentation

Reference Manual PDF

Details

biocViews DifferentialExpression, GeneExpression, GeneRegulation, GeneSetEnrichment, GeneTarget, ImmunoOncology, Microarray, RNASeq, Sequencing, Software
Version 1.28.0
In Bioconductor since BioC 3.4 (R-3.3) (7.5 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
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Package Archives

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

Source Package
Windows Binary eegc_1.28.0.zip
macOS Binary (x86_64) eegc_1.28.0.tgz
macOS Binary (arm64) eegc_1.28.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/eegc
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/eegc
Bioc Package Browser https://code.bioconductor.org/browse/eegc/
Package Short Url https://bioconductor.org/packages/eegc/
Package Downloads Report Download Stats