Doubly stochastic continuous-time hidden Markov approach for analyzing genome tiling arrays

TL;DR

This paper introduces a novel doubly stochastic continuous-time hidden Markov model tailored for analyzing genome tiling array data, effectively addressing artifacts and considering genomic distances to improve transcript and protein binding site detection.

Contribution

The proposed model uniquely incorporates genomic distances and robustness to artifacts, advancing tiling array analysis methods beyond existing approaches.

Findings

High accuracy in transcript and binding site detection

Robustness to cross-hybridization and nonresponsive probes

Effective on single samples without control experiments

Abstract

Microarrays have been developed that tile the entire nonrepetitive genomes of many different organisms, allowing for the unbiased mapping of active transcription regions or protein binding sites across the entire genome. These tiling array experiments produce massive correlated data sets that have many experimental artifacts, presenting many challenges to researchers that require innovative analysis methods and efficient computational algorithms. This paper presents a doubly stochastic latent variable analysis method for transcript discovery and protein binding region localization using tiling array data. This model is unique in that it considers actual genomic distance between probes. Additionally, the model is designed to be robust to cross-hybridized and nonresponsive probes, which can often lead to false-positive results in microarray experiments. We apply our model to a transcript finding data set to illustrate the consistency of our method. Additionally, we apply our method to a spike-in experiment that can be used as a benchmark data set for researchers interested in developing and comparing future tiling array methods. The results indicate that our method is very powerful, accurate and can be used on a single sample and without control experiments, thus defraying some of the overhead cost of conducting experiments on tiling arrays.