title: A nested parallel experiment demonstrates differences in intensity-dependence between RNA-seq and microarrays.
abstract: Understanding the differences between microarray and RNA-Seq technologies for measuring gene expression is necessary for informed design of experiments and choice of data analysis methods. Previous comparisons have come to sometimes contradictory conclusions, which we suggest result from a lack of attention to the intensity-dependent nature of variation generated by the technologies. To examine this trend, we carried out a parallel nested experiment performed simultaneously on the two technologies that systematically split variation into four stages (treatment, biological variation, library preparation and chip/lane noise), allowing a separation and comparison of the sources of variation in a well-controlled cellular system, Saccharomyces cerevisiae. With this novel dataset, we demonstrate that power and accuracy are more dependent on per-gene read depth in RNA-Seq than they are on fluorescence intensity in microarrays. However, we carried out quantitative PCR validations which indicate that microarrays may demonstrate greater systematic bias in low-intensity genes than in RNA-seq.
authors.affiliation: Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
authors.forename: David G
authors.initials: DG
authors.lastname: Robinson
authors.affiliation: Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
authors.forename: Jean Y
authors.initials: JY
authors.lastname: Wang
authors.affiliation: Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA Center for Statistics and Machine Learning, Princeton University, Princeton, NJ 08544, USA Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA jstorey@princeton.edu.
authors.forename: John D
authors.initials: JD
authors.lastname: Storey
mesh_terms: D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods*; D005800:Genes, Fungal; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D016133:Polymerase Chain Reaction; D012441:Saccharomyces cerevisiae / Q000235:genetics; D017423:Sequence Analysis, RNA / Q000379:methods*