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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("RmiR.hsa")
In most cases, you don't need to download the package archive at all.
RmiR.hsa
Various databases of microRNA Targets
Bioconductor version: 3.0
Various databases of microRNA Targets
Author: Francesco Favero
Maintainer: Francesco Favero <favero.francesco at gmail.com>
Citation (from within R,
enter citation("RmiR.hsa")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("RmiR.hsa")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("RmiR.hsa")
| R Script | RmiR.hsa Vignette | |
| RmiRdb-fig1a.pdf | ||
| RmiRdb-fig1b.pdf | ||
| RmiRdb-fig2a.pdf | ||
| RmiRdb-fig2b.pdf | ||
| Reference Manual |
Details
| biocViews | AnnotationData, CustomDBSchema, Homo_sapiens, miRNA |
| Version | 1.0.5 |
| License | The Artistic License, Version 2.0 |
| Depends | R (>= 2.7.0) |
| Imports | AnnotationDbi |
| LinkingTo | |
| Suggests | methods, hgug4112a.db |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | RmiR.hsa_1.0.5.tar.gz |
| Windows Binary | RmiR.hsa_1.0.5.zip |
| Mac OS X 10.6 (Snow Leopard) | RmiR.hsa_1.0.5.tgz |
| Mac OS X 10.9 (Mavericks) | RmiR.hsa_1.0.5.tgz |
| 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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