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Pearson, R., Liu, X., Sanguinetti, G., Milo, M., Lawrence, N. D. and Rattray, M.,
puma: a Bioconductor package for Propagating Uncertainty in Microarray Analysis,
BMC Bioinformatics,
2009 10:211. (featured article, Journal
link )
Liu, X., Lin, K. K., Andersen, B. and Rattray, M., Including probe-level uncertainty
in model-based gene expression clustering, BMC Bioinformatics,
2007 8:98. (Journal
link )
Liu, X., Milo, M., Lawrence, N. D. and Rattray, M., Probe-level
measurement error improves accuracy in detecting differential gene expression,
Bioinformatics,
2006 22(17):
2107-2113. (Journal
link )
Rattray, M., Liu, X., Sanguinetti, G., Milo, M. and Lawrence, N. D.,
Propagating uncertainty in Microarray data analysis, Briefings in Bioinformatics,
2006 7(1):37-47.
(Jounal
link)
Liu, X., Milo, M., Lawrence, N. D. and Rattray, M., A tractable
probabilistic model for Affymetrix probe-level analysis across multiple chips,
Bioinformatics,
2005
21(18):3637-3644. (Jounal
link)
Software
pumaclustii: an R
package to propagate probe-level measurement error in a robust t-mixture clustering model for replicated gene expression
data. (Linux add-on package,
Windows add-on package)
mmgmos: an R
package to estimate the expression levels and the confidence of measures for
multiple arrays of the same type of Affymetrix GeneChips using the multi-chip
modified gamma Model for Oligonucleotide Signal (multi-mgMOS) and the modified
gamma Model for Oligonucleotide Signal (mgMOS).
pplr: an R package to include
probe-level measurement error into the variance estimates of gene expression
levels and to detect up-regulated genes by calculating probability of positive
log-ratio (PPLR).
pumaclust: an R package to propagate
probe-level measurement error in the model-based clustering of gene expression
data.
The above packages, mmgmos, pplr
and pumaclust, have been integrated in a large package puma
which is released by BioConductor.