puma - Propagating Uncertainty in Microarray Analysis

Description

Most analyses of Affymetrix GeneChip data (including tranditional 3' arrays and exon arrays) 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. In additon to calculte gene expression from Affymetrix 3' arrays, puma also provides methods to process exon arrays and produces gene and isoform expression for alternative splicing study. 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 functions.

Details

For details of using the package please refer to the Vignette

Author(s)

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

Maintainer: Richard Pearson <richard.pearson@postgrad.manchester.ac.uk>, Li Zhang <leo.zhang@nuaa.edu.cn>

References

Milo, M., Niranjan, M., Holley, M. C., Rattray, M. and Lawrence, N. D. (2004) A probabilistic approach for summarising oligonucleotide gene expression data, technical report available upon request.

Liu, X., Milo, M., Lawrence, N. D. and Rattray, M. (2005) A tractable probabilistic model for Affymetrix probe-level analysis across multiple chips, Bioinformatics, 21(18):3637-3644.

Sanguinetti, G., Milo, M., Rattray, M. and Lawrence, N. D. (2005) Accounting for probe-level noise in principal component analysis of microarray data, Bioinformatics, 21(19):3748-3754.

Rattray, M., Liu, X., Sanguinetti, G., Milo, M. and Lawrence, N. D. (2006) Propagating uncertainty in Microarray data analysis, Briefings in Bioinformatics, 7(1):37-47.

Liu, X., Milo, M., Lawrence, N. D. and Rattray, M. (2006) Probe-level measurement error improves accuracy in detecting differential gene expression, Bioinformatics, 22(17):2107-2113.

Liu, X. Lin, K., Andersen, B. Rattray, M. (2007) Including probe-level uncertainty in model-based gene expression clustering, BMC Bioinformatics, 8(98).

Pearson, R. D., Liu, X., Sanguinetti, G., Milo, M., Lawrence, N. D., Rattray, M. (2008) puma: a Bioconductor package for Propagating Uncertainty in Microarray Analysis, BMC Bioinformatics, 2009, 10:211.

Zhang,L. and Liu,X. (2009) An improved probabilistic model for finding differential gene expression, the 2nd BMEI 17-19 oct. 2009. Tianjin. China.

Liu,X. and Rattray,M. (2009) Including probe-level measurement error in robust mixture clustering of replicated microarray gene expression, Statistical Application in Genetics and Molecular Biology, 9(1), Article 42.

puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis, Liu et al. BMC Bioinformatics, 2013, 14:39.

Examples

	#	Next 4 lines commented out to save time in package checks, and saved version used
    # if (require(affydata)) {
	#	data(Dilution)
	#	eset_mmgmos <- mmgmos(Dilution)
	# }
	data(eset_mmgmos)
	pumapca_mmgmos <- pumaPCA(eset_mmgmos)
	plot(pumapca_mmgmos)
	eset_mmgmos_100 <- eset_mmgmos[1:100,]
	eset_comb <- pumaComb(eset_mmgmos_100)
        eset_combImproved <- pumaCombImproved(eset_mmgmos_100)
	esetDE <- pumaDE(eset_comb)
        esetDEImproved <- pumaDE(eset_combImproved)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(puma)
Loading required package: oligo
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: oligoClasses
Welcome to oligoClasses version 1.34.0
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: Biostrings
Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: XVector
================================================================================
Welcome to oligo version 1.36.1
================================================================================
Loading required package: mclust
Package 'mclust' version 5.2
Type 'citation("mclust")' for citing this R package in publications.
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/puma/puma-package.Rd_%03d_medium.png", width=480, height=480)
> ### Name: puma-package
> ### Title: puma - Propagating Uncertainty in Microarray Analysis
> ### Aliases: puma-package puma
> ### Keywords: package
> 
> ### ** Examples
> 
> 	#	Next 4 lines commented out to save time in package checks, and saved version used
>     # if (require(affydata)) {
> 	#	data(Dilution)
> 	#	eset_mmgmos <- mmgmos(Dilution)
> 	# }
> 	data(eset_mmgmos)
> 	pumapca_mmgmos <- pumaPCA(eset_mmgmos)
Iteration number: 1
Iteration number: 2
Iteration number: 3
Iteration number: 4
> 	plot(pumapca_mmgmos)
> 	eset_mmgmos_100 <- eset_mmgmos[1:100,]
> 	eset_comb <- pumaComb(eset_mmgmos_100)
Calculating expected completion time
pumaComb expected completion time is 32 seconds 
.......20%.......40%.......60%.......80%......100%
..................................................
>         eset_combImproved <- pumaCombImproved(eset_mmgmos_100)
pumaComb expected completion time is 6 seconds 
.......20%.......40%.......60%.......80%......100%
..................................................
> 	esetDE <- pumaDE(eset_comb)
>         esetDEImproved <- pumaDE(eset_combImproved)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>