title: Estimating differential expression from multiple indicators.
abstract: Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR.
authors.affiliation: Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia, Quretec Ltd, Tartu, Estonia, Centre for Excellence in Translational Medicine, University of Tartu, Tartu, Estonia, Department of Neuroscience and Pharmacology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark and Department of Computer Science, University of Tartu, Tartu, Estonia.
authors.forename: Sten
authors.initials: S
authors.lastname: Ilmjärv
authors.forename: Christian Ansgar
authors.initials: CA
authors.lastname: Hundahl
authors.forename: Riin
authors.initials: R
authors.lastname: Reimets
authors.forename: Margus
authors.initials: M
authors.lastname: Niitsoo
authors.forename: Raivo
authors.initials: R
authors.lastname: Kolde
authors.forename: Jaak
authors.initials: J
authors.lastname: Vilo
authors.forename: Eero
authors.initials: E
authors.lastname: Vasar
authors.forename: Hendrik
authors.initials: H
authors.lastname: Luuk
mesh_terms: D000818:Animals; D015687:Cell Hypoxia; D003080:Cold Temperature; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D020868:Gene Silencing; D051379:Mice; D020411:Oligonucleotide Array Sequence Analysis; D017423:Sequence Analysis, RNA