Moderated statistical tests for assessing differences in tag abundance

• Published in: Bioinformatics Vol. 23; no. 21; pp. 2881 - 2887
• Main Authors: Robinson, Mark D., Smyth, Gordon K.
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01-11-2007; Oxford Publishing Limited (England)
• Subjects: Algorithms; Biological and medical sciences; Computer Simulation; Data Interpretation, Statistical; Expressed Sequence Tags; Fundamental and applied biological sciences. Psychology; Gene Expression Profiling - methods; General aspects; Likelihood Functions; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Models, Genetic; Models, Statistical; Poisson Distribution; Sequence Analysis, DNA - methods; Signal Processing, Computer-Assisted; Statistical test; Test; Bioinformatics
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btm453

Motivation: Digital gene expression (DGE) technologies measure gene expression by counting sequence tags. They are sensitive technologies for measuring gene expression on a genomic scale, without the need for prior knowledge of the genome sequence. As the cost of sequencing DNA decreases, the number of DGE datasets is expected to grow dramatically. Various tests of differential expression have been proposed for replicated DGE data using binomial, Poisson, negative binomial or pseudo-likelihood (PL) models for the counts, but none of the these are usable when the number of replicates is very small. Results: We develop tests using the negative binomial distribution to model overdispersion relative to the Poisson, and use conditional weighted likelihood to moderate the level of overdispersion across genes. Not only is our strategy applicable even with the smallest number of libraries, but it also proves to be more powerful than previous strategies when more libraries are available. The methodology is equally applicable to other counting technologies, such as proteomic spectral counts. Availability: An R package can be accessed from http://bioinf.wehi.edu.au/resources/ Contact: [e-mail] Supplementary information: http://bioinf.wehi.edu.au/resources/