DOTSeq enables genome-wide detection of differential ORF usage

Abstract

Protein synthesis is regulated by multiple cis-regulatory elements, including small ORFs, yet current differential translation methods assume uniform changes at the gene level. We present DOTSeq, a Differential ORF Translation statistical framework that resolves ORF-level regulation in bulk ribosome profiling (Ribo-seq) experiments and provides ORF-level read summarisation for single-cell Ribo-seq. DOTSeqs core module, Differential ORF Usage (DOU), quantifies changes in an ORFs relative contribution to a genes translation output, using a beta-binomial GLM with flexible dispersion modelling. DOTSeq also implements ORF-level Differential Translation Efficiency (DTE) using a standard approach to complement DOU. Benchmarks show that DOU achieves superior sensitivity with near-nominal FDR across effect sizes, while DTE and some existing methods excel when technical noise is low. DOTSeq introduces an ORF-aware, quantitative framework for ribosome profiling, delivering end-to-end workflows for ORF annotation, read summarisation, contrast estimation, and visualisation to uncover translational control events at scale.