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Empirical Bayes Methods for DNA Microarray Data

Lönnstedt, Ingrid, 1975- (författare)
Uppsala universitet,Matematiska institutionen
Gut, Allan (preses)
Britton, Tom (preses)
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Langaas, Mette, Associate professor (opponent)
Institutt for matematiske fag, NTNU, Trondheim
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 (creator_code:org_t)
ISBN 9150618075
Uppsala : Matematiska institutionen, 2005
Engelska xvi + 45 s.
Serie: Uppsala Dissertations in Mathematics, 1401-2049 ; 40
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)
Abstract Ämnesord
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  • cDNA microarrays is one of the first high-throughput gene expression technologies that has emerged within molecular biology for the purpose of functional genomics. cDNA microarrays compare the gene expression levels between cell samples, for thousands of genes simultaneously. The microarray technology offers new challenges when it comes to data analysis, since the thousands of genes are examined in parallel, but with very few replicates, yielding noisy estimation of gene effects and variances. Although careful image analyses and normalisation of the data is applied, traditional methods for inference like the Student t or Fisher’s F-statistic fail to work.In this thesis, four papers on the topics of empirical Bayes and full Bayesian methods for two-channel microarray data (as e.g. cDNA) are presented. These contribute to proving that empirical Bayes methods are useful to overcome the specific data problems. The sample distributions of all the genes involved in a microarray experiment are summarized into prior distributions and improves the inference of each single gene.The first part of the thesis includes biological and statistical background of cDNA microarrays, with an overview of the different steps of two-channel microarray analysis, including experimental design, image analysis, normalisation, cluster analysis, discrimination and hypothesis testing. The second part of the thesis consists of the four papers. Paper I presents the empirical Bayes statistic B, which corresponds to a t-statistic. Paper II is based on a version of B that is extended for linear model effects. Paper III assesses the performance of empirical Bayes models by comparisons with full Bayes methods. Paper IV provides extensions of B to what corresponds to F-statistics.

Ämnesord

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)

Nyckelord

Mathematical statistics
two-channel microarrays
differential expression
replication
empirical Bayes
factorial design
interaction
time trends
hierarchical Bayes
MCMC simulations
ANOVA
F-statistics
Matematisk statistik
Mathematical statistics
Matematisk statistik

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