eegc
Engineering Evaluation by Gene Categorization (eegc)
Bioconductor version: Release (3.17)
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("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
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("eegc")| Engineering Evaluation by Gene Categorization (eegc) | R Script | |
| Reference Manual |
Details
| biocViews | DifferentialExpression, GeneExpression, GeneRegulation, GeneSetEnrichment, GeneTarget, ImmunoOncology, Microarray, RNASeq, Sequencing, Software |
| Version | 1.26.0 |
| In Bioconductor since | BioC 3.4 (R-3.3) (7 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 |
| Linking To | |
| Suggests | knitr |
| System Requirements | |
| Enhances | |
| URL |
See More
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | eegc_1.26.0.tar.gz |
| Windows Binary | eegc_1.26.0.zip (64-bit only) |
| macOS Binary (x86_64) | eegc_1.26.0.tgz |
| macOS Binary (arm64) | eegc_1.26.0.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 |