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BioinformaticsBioinformaticsPeer-reviewed journal article

HRIBO - High-throughput analysis of bacterial ribosome profiling data

Rick GelhauseniD, Sarah L. SvenssoniD, Kathrin FroschaueriD, Florian HeyliD, Lydia HadjerasiD, Cynthia Mira SharmaiD, Florian EggenhoferiD, Rolf BackofeniD

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Citations
17
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0.81
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top 32%

Abstract

MotivationRibosome profiling (Ribo-seq) is a powerful approach based on ribosome-protected RNA fragments to explore the translatome of a cell, and is especially useful for the detection of small proteins (<=70 amino acids) that are recalcitrant to biochemical and in silico approaches. While pipelines are available to analyze Ribo-seq data, none are designed explicitly for the analysis of Ribo-seq data from prokaryotes, nor are they focused on the discovery of unannotated open reading frames (ORFs) in bacteria. ResultsWe present HRIBO (High-throughput annotation by Ribo-seq), a workflow to enable reproducible and high-throughput analysis of bacterial Ribo-seq data. The workflow performs all required pre-processing and quality control steps. Importantly, HRIBO outputs annotation-independent ORF predictions based on two complementary bacteria-focused tools, and integrates them with additional features. This facilitates the rapid discovery of novel ORFs and their prioritization for functional characterization. AvailabilityHRIBO is a free and open source project available under the GPL-3 license at: https://github.com/RickGelhausen/HRIBO

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Rick Gelhausen, Teresa Müller, Sarah L. Svensson+4 more·Briefings in Bioinformatics·Dec 1, 2021· 26 citations