RNAsense
This is the released version of RNAsense; for the devel version, see RNAsense.
Analysis of Time-Resolved RNA-Seq Data
Bioconductor version: Release (3.23)
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("RNAsense")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") 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 |
Details
| biocViews | DifferentialExpression, GeneExpression, RNASeq, Software |
| Version | 1.26.0 |
| In Bioconductor since | BioC 3.10 (R-3.6) (7 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 |
See More
| Suggests | knitr, rmarkdown |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | RNAsense_1.26.0.tar.gz |
| Windows Binary (x86_64) | RNAsense_1.26.0.zip (64-bit only) |
| macOS Binary (big-sur-x86_64) | RNAsense_1.26.0.tgz |
| macOS Binary (sonoma-arm64) | RNAsense_1.26.0.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 |