Differential expression in SAGE: accounting for normal between-library variation

Motivation: In contrasting levels of gene expression between groups of SAGE libraries, the libraries within each group are often combined and the counts for the tag of interest summed, and inference is made on the basis of these larger ‘pseudolibraries’. While this captures the sampling variability...

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Veröffentlicht in:Bioinformatics 2003-08, Vol.19 (12), p.1477-1483
Hauptverfasser: Baggerly, Keith A., Deng, Li, Morris, Jeffrey S., Aldaz, C. Marcelo
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container_end_page 1483
container_issue 12
container_start_page 1477
container_title Bioinformatics
container_volume 19
creator Baggerly, Keith A.
Deng, Li
Morris, Jeffrey S.
Aldaz, C. Marcelo
description Motivation: In contrasting levels of gene expression between groups of SAGE libraries, the libraries within each group are often combined and the counts for the tag of interest summed, and inference is made on the basis of these larger ‘pseudolibraries’. While this captures the sampling variability inherent in the procedure, it fails to allow for normal variation in levels of the gene between individuals within the same group, and can consequently overstate the significance of the results. The effect is not slight: between-library variation can be hundreds of times the within-library variation. Results: We introduce a beta-binomial sampling model that correctly incorporates both sources of variation. We show how to fit the parameters of this model, and introduce a test statistic for differential expression similar to a two-sample t-test. Contact: kabagg@mdanderson.org Supplementary information http://bioinformatics.mdanderson.org/ Includes Matlab and R code for fitting the model. * To whom correspondence should be addressed.
doi_str_mv 10.1093/bioinformatics/btg173
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source MEDLINE; Oxford Journals Open Access Collection; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection
subjects Algorithms
Biological and medical sciences
Expressed Sequence Tags
Fundamental and applied biological sciences. Psychology
Gene Expression Profiling - methods
Gene Library
General aspects
Genetic Variation
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Models, Genetic
Models, Statistical
Reproducibility of Results
Sensitivity and Specificity
Sequence Analysis, DNA - methods
title Differential expression in SAGE: accounting for normal between-library variation
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