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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("LVSmiRNA")
In most cases, you don't need to download the package archive at all.
LVSmiRNA
LVS normalization for Agilent miRNA data
Bioconductor version: 3.0
Normalization of Agilent miRNA arrays.
Author: Stefano Calza, Suo Chen, Yudi Pawitan
Maintainer: Stefano Calza <stefano.calza at unibs.it>
Citation (from within R,
enter citation("LVSmiRNA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("LVSmiRNA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("LVSmiRNA")
| R Script | LVSmiRNA | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | AgilentChip, Microarray, OneChannel, Preprocessing, Software |
| Version | 1.16.0 |
| In Bioconductor since | BioC 2.7 (R-2.12) |
| License | GPL-2 |
| Depends | R (>= 3.1.0), methods, splines |
| Imports | BiocGenerics, stats4, graphics, stats, utils, MASS, Biobase, quantreg, limma, affy, SparseM, vsn |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | parallel, snow, Rmpi |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | LVSmiRNA_1.16.0.tar.gz |
| Windows Binary | LVSmiRNA_1.16.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | LVSmiRNA_1.16.0.tgz |
| Mac OS X 10.9 (Mavericks) | LVSmiRNA_1.16.0.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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