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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("maigesPack")
In most cases, you don't need to download the package archive at all.
maigesPack
Functions to handle cDNA microarray data, including several methods of data analysis
Bioconductor version: 3.0
This package uses functions of various other packages together with other functions in a coordinated way to handle and analyse cDNA microarray data
Author: Gustavo H. Esteves <gesteves at gmail.com>, with contributions from Roberto Hirata Jr <hirata at ime.usp.br>, E. Jordao Neves <neves at ime.usp.br>, Elier B. Cristo <elier at ime.usp.br>, Ana C. Simoes <anakqui at ime.usp.br> and Lucas Fahham <fahham at linux.ime.usp.br>
Maintainer: Gustavo H. Esteves <gesteves at gmail.com>
Citation (from within R,
enter citation("maigesPack")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("maigesPack")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("maigesPack")
| R Script | maigesPack Tutorial | |
| Reference Manual |
Details
| biocViews | Classification, Clustering, DifferentialExpression, GraphAndNetwork, Microarray, Preprocessing, Software, ThirdPartyClient, TwoChannel |
| Version | 1.30.0 |
| In Bioconductor since | BioC 2.1 (R-2.6) |
| License | GPL (>= 2) |
| Depends | R (>= 2.10), convert, graph, limma, marray, methods |
| Imports | |
| LinkingTo | |
| Suggests | amap, annotate, class, e1071, MASS, multtest, OLIN, R2HTML, rgl, som |
| SystemRequirements | |
| Enhances | |
| URL | http://www.maiges.org/en/software/ |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | maigesPack_1.30.0.tar.gz |
| Windows Binary | maigesPack_1.30.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | maigesPack_1.30.0.tgz |
| Mac OS X 10.9 (Mavericks) | maigesPack_1.30.0.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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