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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("SpeCond")
In most cases, you don't need to download the package archive at all.
SpeCond
Condition specific detection from expression data
Bioconductor version: 3.0
This package performs a gene expression data analysis to detect condition-specific genes. Such genes are significantly up- or down-regulated in a small number of conditions. It does so by fitting a mixture of normal distributions to the expression values. Conditions can be environmental conditions, different tissues, organs or any other sources that you wish to compare in terms of gene expression.
Author: Florence Cavalli
Maintainer: Florence Cavalli <florence at ebi.ac.uk>
Citation (from within R,
enter citation("SpeCond")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("SpeCond")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("SpeCond")
| R Script | SpeCond | |
| Reference Manual |
Details
| biocViews | Clustering, DifferentialExpression, Microarray, MultipleComparison, ReportWriting, Software |
| Version | 1.20.0 |
| In Bioconductor since | BioC 2.5 (R-2.10) |
| License | LGPL (>=2) |
| Depends | R (>= 2.10.0), mclust (>= 3.3.1), Biobase(>= 1.15.13), fields, hwriter (>= 1.1), RColorBrewer, methods |
| Imports | |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| 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 | SpeCond_1.20.0.tar.gz |
| Windows Binary | SpeCond_1.20.0.zip |
| Mac OS X 10.6 (Snow Leopard) | SpeCond_1.20.0.tgz |
| Mac OS X 10.9 (Mavericks) | SpeCond_1.20.0.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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