Transcriptional landscape estimation from tiling array data using a model of signal shift and drift.

ABSTRACT:

Motivation

High-density oligonucleotide tiling array technology holds the promise of a better description of the complexity and the dynamics of transcriptional landscapes. In organisms such as bacteria and yeasts, transcription can be measured on a genome-wide scale with a resolution >25 bp. The statistical models currently used to handle these data remain however very simple, the most popular being the piecewise constant Gaussian model with a fixed number of breakpoints.

Results

This article describes a new methodology based on a hidden Markov model that embeds the segmentation of a continuous-valued signal in a probabilistic setting. For a computationally affordable cost, this framework (i) alleviates the difficulty of choosing a fixed number of breakpoints, and (ii) permi

SUBMITTER: Nicolas P 

PROVIDER: S-EPMC2735659 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature