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 between microarrays and RNA-Seq have come to sometimes contradictory conclusions, which researchers from Princeton University suggest result from a lack of attention to the intensity-dependent nature of variation generated by the technologies. To examine this trend, they 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.

Schematic of the experiment. The Condition and Biological Replicate steps were performed irrespective of technology and these materials were then utilized in a technology-specific manner (microarrays or RNA-seq) for the Preparation and Chip/Lane steps.

With this novel dataset, the researchers 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, they carried out quantitative PCR validations which indicate that microarrays may demonstrate greater systematic bias in low-intensity genes than in RNA-seq.

Percent of variance explained by each nested level of the experiment as computed by an ANOVA adjusted R², and smoothed using LOESS across the intensity quantiles. Results from microarray data (MA) are shown in the solid lines and RNA-Seq data (RS) in the dashed lines. A 95% confidence interval is shown as the shaded region around each line.