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blima

Tools for the preprocessing and analysis of the Illumina microarrays on the detector (bead) level


Bioconductor version: Release (3.18)

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: Vojtěch Kulvait

Maintainer: Vojtěch Kulvait <kulvait at gmail.com>

Citation (from within R, enter citation("blima")):

Installation

To install this package, start R (version "4.3") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("blima")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("blima")
blima.pdf PDF R Script
Reference Manual PDF
NEWS Text

Details

biocViews DifferentialExpression, GeneExpression, GeneRegulation, Microarray, Normalization, Preprocessing, Software
Version 1.36.0
In Bioconductor since BioC 3.0 (R-3.1) (9.5 years)
License GPL-3
Depends R (>= 3.3)
Imports beadarray(>= 2.0.0), Biobase(>= 2.0.0), Rcpp (>= 0.12.8), BiocGenerics, grDevices, stats, graphics
System Requirements
URL https://bitbucket.org/kulvait/blima
See More
Suggests xtable, blimaTestingData, BiocStyle, illuminaHumanv4.db, lumi, knitr
Linking To Rcpp
Enhances
Depends On Me
Imports Me
Suggests Me blimaTestingData
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package blima_1.36.0.tar.gz
Windows Binary blima_1.36.0.zip
macOS Binary (x86_64) blima_1.36.0.tgz
macOS Binary (arm64) blima_1.36.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/blima
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/blima
Bioc Package Browser https://code.bioconductor.org/browse/blima/
Package Short Url https://bioconductor.org/packages/blima/
Package Downloads Report Download Stats