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RNAsense

Analysis of Time-Resolved RNA-Seq Data


Bioconductor version: Release (3.18)

RNA-sense tool compares RNA-seq time curves in two experimental conditions, i.e. wild-type and mutant, and works in three steps. At Step 1, it builds expression profile for each transcript in one condition (i.e. wild-type) and tests if the transcript abundance grows or decays significantly. Dynamic transcripts are then sorted to non-overlapping groups (time profiles) by the time point of switch up or down. At Step 2, RNA-sense outputs the groups of differentially expressed transcripts, which are up- or downregulated in the mutant compared to the wild-type at each time point. At Step 3, Correlations (Fisher's exact test) between the outputs of Step 1 (switch up- and switch down- time profile groups) and the outputs of Step2 (differentially expressed transcript groups) are calculated. The results of the correlation analysis are printed as two-dimensional color plot, with time profiles and differential expression groups at y- and x-axis, respectively, and facilitates the biological interpretation of the data.

Author: Marcus Rosenblatt [cre], Gao Meijang [aut], Helge Hass [aut], Daria Onichtchouk [aut]

Maintainer: Marcus Rosenblatt <marcus.rosenblatt at gmail.com>

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

Installation

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


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

BiocManager::install("RNAsense")

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("RNAsense")
Put the title of your vignette here HTML R Script
Reference Manual PDF

Details

biocViews DifferentialExpression, GeneExpression, RNASeq, Software
Version 1.16.0
In Bioconductor since BioC 3.10 (R-3.6) (4.5 years)
License GPL-3
Depends R (>= 3.6)
Imports ggplot2, parallel, NBPSeq, qvalue, SummarizedExperiment, stats, utils, methods
System Requirements
URL
Bug Reports https://github.com/marcusrosenblatt/RNAsense
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Suggests knitr, rmarkdown
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Package Archives

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

Source Package RNAsense_1.16.0.tar.gz
Windows Binary RNAsense_1.16.0.zip
macOS Binary (x86_64) RNAsense_1.16.0.tgz
macOS Binary (arm64) RNAsense_1.16.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/RNAsense
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/RNAsense
Bioc Package Browser https://code.bioconductor.org/browse/RNAsense/
Package Short Url https://bioconductor.org/packages/RNAsense/
Package Downloads Report Download Stats