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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MmPalateMiRNA")
In most cases, you don't need to download the package archive at all.
MmPalateMiRNA
Murine Palate miRNA Expression Analysis
Bioconductor version: 2.14
R package compendium for the analysis of murine palate miRNA two-color expression data.
Author: Guy Brock <guy.brock at louisville.edu>, Partha Mukhopadhyay <p0mukh01 at louisville.edu>, Vasyl Pihur <vasyl.pihur at louisville.edu>, Robert M. Greene <Dr.Bob.Greene at gmail.com>, and M. Michele Pisano <mmpisa01 at louisville.edu>
Maintainer: Guy Brock <guy.brock at louisville.edu>
Citation (from within R,
enter citation("MmPalateMiRNA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MmPalateMiRNA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("MmPalateMiRNA")
| R Script | Palate miRNA Analysis | |
| Reference Manual |
Details
| biocViews | Clustering, DifferentialExpression, GO, Microarray, MultipleComparison, Pathways, Preprocessing, QualityControl, ReportWriting, SequenceMatching, Software, TwoChannel |
| Version | 1.14.0 |
| In Bioconductor since | BioC 2.9 (R-2.14) |
| License | GPL-3 |
| Depends | R (>= 2.13.0), methods, Biobase, xtable, limma, statmod, lattice, vsn |
| Imports | limma, lattice, Biobase |
| Suggests | GOstats, graph, Category, org.Mm.eg.db, microRNA, targetscan.Mm.eg.db, RSQLite, DBI, AnnotationDbi, clValid, class, cluster, multtest, RColorBrewer, latticeExtra |
| System Requirements | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | MmPalateMiRNA_1.14.0.tar.gz |
| Windows Binary | MmPalateMiRNA_1.14.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | MmPalateMiRNA_1.14.0.tgz |
| Mac OS X 10.9 (Mavericks) | MmPalateMiRNA_1.14.0.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
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