Propagating Uncertainty in Microarray Analysis

Bioconductor version: 2.9

Most analyses of Affymetrix GeneChip data are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting and data manipulation functions.

Author: Richard D. Pearson, Xuejun Liu, Magnus Rattray, Marta Milo, Neil D. Lawrence, Guido Sanguinetti, Li Zhang

Maintainer: Richard Pearson <richard.pearson at well.ox.ac.uk>

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PDF puma-014.pdf
PDF puma-015.pdf
PDF puma-016.pdf
PDF puma-022.pdf
PDF puma-023.pdf
PDF puma-024.pdf
PDF puma.pdf
PDF   Reference Manual


biocViews Microarray, OneChannel, Preprocessing, Bioinformatics, DifferentialExpression, Clustering
Depends R (>= 2.6.0), Biobase(>= 2.5.5), affy(>= 1.23.4), graphics, grDevices, methods, stats, utils, mclust
Imports Biobase(>= 2.5.5), affy(>= 1.23.4)
Suggests pumadata, affydata, snow, limma, annotate, ROCR
System Requirements
License LGPL
URL http://umber.sbs.man.ac.uk/resources/puma
Depends On Me pumadata
Imports Me tigre
Suggests Me tigre
Version 2.6.0
Since Bioconductor 2.0 (R-2.5)

Package Downloads

Package Source puma_2.6.0.tar.gz
Windows Binary puma_2.6.0.zip (32- & 64-bit)
MacOS 10.5 (Leopard) binary puma_2.6.0.tgz
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