Segmentor3IsBack: an R package for the fast and exact segmentation of Seq-data

TL;DR

Segmentor3IsBack is an R package that efficiently segments RNA-Seq data to identify gene boundaries using a modified Pruned Dynamic Programming Algorithm tailored for negative binomial models, demonstrating good performance on real data.

Contribution

The paper introduces a fast, exact segmentation method for RNA-Seq data using an adapted PDP algorithm for negative binomial distributions, with an implementation available as an R package.

Findings

Effective segmentation of RNA-Seq data demonstrated on real datasets.

The adapted PDP algorithm performs well with known dispersion.

The package is available on CRAN for broad use.

Abstract

Genome annotation is an important issue in biology which has long been addressed with gene prediction methods and manual experiments requiring biological expertise. The expanding Next Generation Sequencing technologies and their enhanced precision allow a new approach to the domain: the segmentation of RNA-Seq data to determine gene boundaries. Because of its almost linear complexity, we propose to use the Pruned Dynamic Programming Algorithm, which performances had been acknowledged for CGH arrays, for Seq-experiment outputs. This requires the adaptation of the algorithm to the negative binomial distribution with which we model the data. We show that if the dispersion in the signal is known, the PDP algorithm can be used and we provide an estimator for this dispersion. We then propose to estimate the number of segments, which can be associated to coding or non-coding regions of the genome, using an oracle penalty. We illustrate the results of our approach on a real data-set and show its good performance. Our algorithm is available as an R package on the CRAN repository.