To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("piano")
In most cases, you don't need to download the package archive at all.
piano
Platform for integrative analysis of omics data
Bioconductor version: 3.0
Piano performs gene set analysis using various statistical methods, from different gene level statistics and a wide range of gene-set collections. Furthermore, the Piano package contains functions for combining the results of multiple runs of gene set analyses.
Author: Leif Varemo <piano.rpkg at gmail.com> and Intawat Nookaew <piano.rpkg at gmail.com>
Maintainer: Leif Varemo <piano.rpkg at gmail.com>
Citation (from within R,
enter citation("piano")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("piano")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("piano")
| R Script | Piano - Platform for Integrative Analysis of Omics data | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | DifferentialExpression, GeneExpression, GeneSetEnrichment, Microarray, Pathways, Preprocessing, QualityControl, Software, Visualization |
| Version | 1.6.2 |
| In Bioconductor since | BioC 2.12 (R-3.0) |
| License | GPL (>=2) |
| Depends | R (>= 2.14.0) |
| Imports | Biobase, gplots, igraph, relations, marray |
| LinkingTo | |
| Suggests | yeast2.db, rsbml, plotrix, limma, affy, plier, affyPLM, gtools, biomaRt, snowfall |
| SystemRequirements | |
| Enhances | |
| URL | http://www.sysbio.se/piano |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | piano_1.6.2.tar.gz |
| Windows Binary | piano_1.6.2.zip |
| Mac OS X 10.6 (Snow Leopard) | piano_1.6.2.tgz |
| Mac OS X 10.9 (Mavericks) | piano_1.6.2.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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