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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("Harshlight")
In most cases, you don't need to download the package archive at all.
Harshlight
A "corrective make-up" program for microarray chips
Bioconductor version: 3.0
The package is used to detect extended, diffuse and compact blemishes on microarray chips. Harshlight automatically marks the areas in a collection of chips (affybatch objects) and a corrected AffyBatch object is returned, in which the defected areas are substituted with NAs or the median of the values of the same probe in the other chips in the collection. The new version handle the substitute value as whole matrix to solve the memory problem.
Author: Mayte Suarez-Farinas, Maurizio Pellegrino, Knut M. Wittkowski, Marcelo O. Magnasco
Maintainer: Maurizio Pellegrino <mpellegri at berkeley.edu>
Citation (from within R,
enter citation("Harshlight")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("Harshlight")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("Harshlight")
| R Script | Harshlight | |
| Reference Manual |
Details
| biocViews | Microarray, OneChannel, Preprocessing, QualityControl, ReportWriting, Software |
| Version | 1.38.0 |
| In Bioconductor since | BioC 1.9 (R-2.4) |
| License | GPL (>= 2) |
| Depends | R (>= 2.10) |
| Imports | affy, altcdfenvs, Biobase, stats, utils |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | http://asterion.rockefeller.edu/Harshlight/ |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | Harshlight_1.38.0.tar.gz |
| Windows Binary | Harshlight_1.38.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | Harshlight_1.38.0.tgz |
| Mac OS X 10.9 (Mavericks) | Harshlight_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
- 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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