To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("blima")
In most cases, you don't need to download the package archive at all.
blima
Package for the preprocessing and analysis of the Illumina microarrays on the detector (bead) level.
Bioconductor version: 3.0
Package blima includes several algorithms for the preprocessing of Illumina microarray data. It focuses to the bead level analysis and provides novel approach to the quantile normalization of the vectors of unequal lengths. It provides variety of the methods for background correction including background subtraction, RMA like convolution and background outlier removal. It also implements variance stabilizing transformation on the bead level. There are also implemented methods for data summarization. It also provides the methods for performing T-tests on the detector (bead) level and on the probe level for differential expression testing.
Author: Vojtech Kulvait
Maintainer: Vojtech Kulvait <kulvait at gmail.com>
Citation (from within R,
enter citation("blima")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("blima")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("blima")
| R Script | blima.pdf | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Microarray, Normalization, Preprocessing, Software |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | GPL-3 |
| Depends | R (>= 3.0.0) |
| Imports | beadarray(>= 2.0.0), Biobase(>= 2.0.0), BiocGenerics, grDevices, stats, graphics |
| LinkingTo | |
| Suggests | xtable, blimaTestingData, BiocStyle, illuminaHumanv4.db, lumi |
| SystemRequirements | |
| Enhances | |
| URL | https://bitbucket.org/kulvait/blima |
| Depends On Me | |
| Imports Me | |
| Suggests Me | blimaTestingData |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | blima_1.0.0.tar.gz |
| Windows Binary | blima_1.0.0.zip |
| Mac OS X 10.6 (Snow Leopard) | blima_1.0.0.tgz |
| Mac OS X 10.9 (Mavericks) | blima_1.0.0.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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