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Roleswitch
Infer miRNA-mRNA interactions using paired expression data from a single sample
Bioconductor version: 3.0
Infer Probabilities of MiRNA-mRNA Interaction Signature (ProMISe) using paired expression data from a single sample. Roleswitch operates in two phases by inferring the probability of mRNA (miRNA) being the targets ("targets") of miRNA (mRNA), taking into account the expression of all of the mRNAs (miRNAs) due to their potential competition for the same miRNA (mRNA). Due to dynamic miRNA repression in the cell, Roleswitch assumes that the total transcribed mRNA levels are higher than the observed (equilibrium) mRNA levels and iteratively updates the total transcription of each mRNA targets based on the above inference. NB: in the paper, we used ProMISe as both the model name and inferred score name.
Author: Yue Li
Maintainer: Yue Li <yueli at cs.toronto.edu>
Citation (from within R,
enter citation("Roleswitch")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("Roleswitch")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("Roleswitch")
| R Script | Roleswitch | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Software, miRNA |
| Version | 1.4.1 |
| In Bioconductor since | BioC 2.13 (R-3.0) |
| License | GPL-2 |
| Depends | R (>= 2.10), pracma, reshape, plotrix, microRNA, biomaRt, Biostrings, Biobase, DBI |
| Imports | |
| LinkingTo | |
| Suggests | ggplot2 |
| SystemRequirements | |
| Enhances | |
| URL | http://www.cs.utoronto.ca/~yueli/roleswitch.html |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | Roleswitch_1.4.1.tar.gz |
| Windows Binary | Roleswitch_1.4.1.zip |
| Mac OS X 10.6 (Snow Leopard) | Roleswitch_1.4.1.tgz |
| Mac OS X 10.9 (Mavericks) | Roleswitch_1.4.1.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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