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Updated: May 13, 2026

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
Published on: February 18, 2022
ORFcor: identifying and accommodating ORF prediction inconsistencies for phylogenetic analysis
Jonathan L Klassen1, Cameron R Currie
1Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, USA. jlklassen@wisc.edu
Abstract:
The high-throughput annotation of open reading frames (ORFs) required by modern genome sequencing projects necessitates computational protocols that sometimes annotate orthologous ORFs inconsistently. Such inconsistencies hinder comparative analyses by non-uniformly extending or truncating 5' and/or 3' sequence ends, causing ORFs that are in fact identical to artificially diverge. Whereas strategies exist to correct such inconsistencies during whole-genome annotation, equivalent software designed to correct subsets of these data without genome reannotation is lacking. We therefore developed ORFcor, which corrects annotation inconsistencies using consensus start and stop positions derived from sets of closely related orthologs. ORFcor corrects inconsistent ORF annotations in diverse test datasets with specificities and sensitivities approaching 100% when sufficiently related orthologs (e.g., from the same taxonomic family) are available for comparison. The ORFcor package is implemented in Perl, multithreaded to handle large datasets, includes related scripts to facilitate high-throughput phylogenomic analyses, and is freely available at www.currielab.wisc.edu/downloads.html.
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