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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("spotSegmentation")
In most cases, you don't need to download the package archive at all.
spotSegmentation
Microarray Spot Segmentation and Gridding for Blocks of Microarray Spots
Bioconductor version: 2.14
Spot segmentation via model-based clustering and gridding for blocks within microarray slides, as described in Li et al, Robust Model-Based Segmentation of Microarray Images, Technical Report no. 473, Department of Statistics, University of Washington.
Author: Qunhua Li, Chris Fraley, Adrian Raftery Department of Statistics, University of Washington
Maintainer: Chris Fraley <fraley at stat.washington.edu>
Citation (from within R,
enter citation("spotSegmentation")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("spotSegmentation")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("spotSegmentation")
| Reference Manual |
Details
| biocViews | Microarray, Preprocessing, QualityControl, Software, TwoChannel |
| Version | 1.38.0 |
| In Bioconductor since | BioC 1.6 (R-2.1) or earlier |
| License | GPL (>= 2) |
| Depends | R (>= 2.10), mclust |
| Imports | |
| Suggests | |
| System Requirements | |
| URL | http://www.stat.washington.edu/fraley |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | spotSegmentation_1.38.0.tar.gz |
| Windows Binary | spotSegmentation_1.38.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | spotSegmentation_1.38.0.tgz |
| Mac OS X 10.9 (Mavericks) | spotSegmentation_1.38.0.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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