Propagating uncertainty in microarray data analysis.

Propagating uncertainty in microarray data analysis. Research Abstract Details 

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Propagating uncertainty in microarray data analysis. Abstract Text:

Magnus Rattray,Xuejun Liu,Guido Sanguinetti,Marta Milo,Neil D Lawrence,Magnus Rattray,Xuejun Liu,Guido Sanguinetti,Marta Milo,Neil D Lawrence,

Microarray technology is associated with many sources of experimental uncertainty. In this review we discuss a number of approaches for dealing with this uncertainty in the processing of data from microarray experiments. We focus here on the analysis of high-density oligonucleotide arrays, such as the popular Affymetrix GeneChip array, which contain multiple probes for each target. This set of probes can be used to determine an estimate for the target concentration and can also be used to determine the experimental uncertainty associated with this measurement. This measurement uncertainty can then be propagated through the downstream analysis using probabilistic methods. We give examples showing how these credibility intervals can be used to help identify differential expression, to combine information from replicated experiments and to improve the performance of principal component analysis.

Propagating uncertainty in microarray data analysis. Publishing Authors By Initials

M Rattray,X Liu,G Sanguinetti,M Milo,ND Lawrence,M Rattray,X Liu,G Sanguinetti,M Milo,ND Lawrence,

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Propagating uncertainty in microarray data analysis. Journal Published:

PUBLICATION TYPE: Review

Journal: Briefings in bioinformatics

VOLUME: 7

Page Numbers: 37-47

Journal Abbreviation: Brief. Bioinformatics

ISSN: 1467-5463

DAY: 9

MONTH: Mar

YEAR: 2006

Propagating uncertainty in microarray data analysis. Information

Number of References: 39

LANGUAGE: eng

NlmUniqueID: 100912837

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AFFILIATION: School of Computer Science, University of Manchester, Manchester M13 9PL, UK. magnus.rattary@manchester.ac.uk

Country: England

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MEDLINETA: Brief Bioinform

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