TEKRABber

An R package estimates the correlations of orthologs and transposable elements between two species


Bioconductor version: Release (3.20)

TEKRABber is made to provide a user-friendly pipeline for comparing orthologs and transposable elements (TEs) between two species. It considers the orthology confidence between two species from BioMart to normalize expression counts and detect differentially expressed orthologs/TEs. Then it provides one to one correlation analysis for desired orthologs and TEs. There is also an app function to have a first insight on the result. Users can prepare orthologs/TEs RNA-seq expression data by their own preference to run TEKRABber following the data structure mentioned in the vignettes.

Author: Yao-Chung Chen [aut, cre] , Katja Nowick [aut]

Maintainer: Yao-Chung Chen <yao-chung.chen at fu-berlin.de>

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

Installation

To install this package, start R (version "4.4") and enter:


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

BiocManager::install("TEKRABber")

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("TEKRABber")
TEKRABber HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DifferentialExpression, GeneExpression, Normalization, Software, Transcription
Version 1.10.0
In Bioconductor since BioC 3.15 (R-4.2) (2.5 years)
License LGPL (>=3)
Depends R (>= 4.3)
Imports apeglm, biomaRt, dplyr, doParallel, DESeq2, foreach, GenomeInfoDb, magrittr, Rcpp (>= 1.0.7), rtracklayer, SCBN, stats, utils
System Requirements
URL https://github.com/ferygood/TEKRABber
Bug Reports https://github.com/ferygood/TEKRABber/issues
See More
Suggests BiocStyle, bslib, ggplot2, ggpubr, plotly, rmarkdown, shiny, knitr, testthat (>= 3.0.0)
Linking To Rcpp
Enhances
Depends On Me
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Package Archives

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

Source Package TEKRABber_1.10.0.tar.gz
Windows Binary (x86_64) TEKRABber_1.10.0.zip
macOS Binary (x86_64) TEKRABber_1.10.0.tgz
macOS Binary (arm64) TEKRABber_1.9.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/TEKRABber
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/TEKRABber
Bioc Package Browser https://code.bioconductor.org/browse/TEKRABber/
Package Short Url https://bioconductor.org/packages/TEKRABber/
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