Statistical metrics for quality assessment of high-density tiling array data

High-density tiling arrays are designed to blanket an entire genomic region of interest using tiled oligonucleotides at very high resolution and are widely used in various biological applications. Experiments are usually conducted in multiple stages, in which unwanted technical variations may be introduced. As tiling arrays become more popular and are adopted by many research labs, it is pressing to develop quality control tools as was done for expression microarrays. We propose a set of statistical quality metrics analogous to those in expression microarrays with application to tiling array data. We also develop a method to estimate the significance level of an observed quality measurement using randomization tests. These methods have been applied to multiple real data sets, including three independent ChIP-chip experiments and one transcriptom mapping study, and they have successfully identified good quality chips as well as outliers in each study.