Cargando…
HRIBO: high-throughput analysis of bacterial ribosome profiling data
MOTIVATION: Ribosome profiling (Ribo-seq) is a powerful approach based on deep sequencing of cDNA libraries generated from ribosome-protected RNA fragments to explore the translatome of a cell, and is especially useful for the detection of small proteins (50–100 amino acids) that are recalcitrant to...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8337001/ https://www.ncbi.nlm.nih.gov/pubmed/33175953 http://dx.doi.org/10.1093/bioinformatics/btaa959 |
_version_ | 1783733420323504128 |
---|---|
author | Gelhausen, Rick Svensson, Sarah L Froschauer, Kathrin Heyl, Florian Hadjeras, Lydia Sharma, Cynthia M Eggenhofer, Florian Backofen, Rolf |
author_facet | Gelhausen, Rick Svensson, Sarah L Froschauer, Kathrin Heyl, Florian Hadjeras, Lydia Sharma, Cynthia M Eggenhofer, Florian Backofen, Rolf |
author_sort | Gelhausen, Rick |
collection | PubMed |
description | MOTIVATION: Ribosome profiling (Ribo-seq) is a powerful approach based on deep sequencing of cDNA libraries generated from ribosome-protected RNA fragments to explore the translatome of a cell, and is especially useful for the detection of small proteins (50–100 amino acids) that are recalcitrant to many standard biochemical and in silico approaches. While pipelines are available to analyze Ribo-seq data, none are designed explicitly for the automatic processing and analysis of data from bacteria, nor are they focused on the discovery of unannotated open reading frames (ORFs). RESULTS: We 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 feature information and expression values. This facilitates the rapid and high-confidence discovery of novel ORFs and their prioritization for functional characterization. AVAILABILITY AND IMPLEMENTATION: HRIBO is a free and open source project available under the GPL-3 license at: https://github.com/RickGelhausen/HRIBO. |
format | Online Article Text |
id | pubmed-8337001 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-83370012021-08-09 HRIBO: high-throughput analysis of bacterial ribosome profiling data Gelhausen, Rick Svensson, Sarah L Froschauer, Kathrin Heyl, Florian Hadjeras, Lydia Sharma, Cynthia M Eggenhofer, Florian Backofen, Rolf Bioinformatics Applications Notes MOTIVATION: Ribosome profiling (Ribo-seq) is a powerful approach based on deep sequencing of cDNA libraries generated from ribosome-protected RNA fragments to explore the translatome of a cell, and is especially useful for the detection of small proteins (50–100 amino acids) that are recalcitrant to many standard biochemical and in silico approaches. While pipelines are available to analyze Ribo-seq data, none are designed explicitly for the automatic processing and analysis of data from bacteria, nor are they focused on the discovery of unannotated open reading frames (ORFs). RESULTS: We 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 feature information and expression values. This facilitates the rapid and high-confidence discovery of novel ORFs and their prioritization for functional characterization. AVAILABILITY AND IMPLEMENTATION: HRIBO is a free and open source project available under the GPL-3 license at: https://github.com/RickGelhausen/HRIBO. Oxford University Press 2020-11-11 /pmc/articles/PMC8337001/ /pubmed/33175953 http://dx.doi.org/10.1093/bioinformatics/btaa959 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Gelhausen, Rick Svensson, Sarah L Froschauer, Kathrin Heyl, Florian Hadjeras, Lydia Sharma, Cynthia M Eggenhofer, Florian Backofen, Rolf HRIBO: high-throughput analysis of bacterial ribosome profiling data |
title | HRIBO: high-throughput analysis of bacterial ribosome profiling data |
title_full | HRIBO: high-throughput analysis of bacterial ribosome profiling data |
title_fullStr | HRIBO: high-throughput analysis of bacterial ribosome profiling data |
title_full_unstemmed | HRIBO: high-throughput analysis of bacterial ribosome profiling data |
title_short | HRIBO: high-throughput analysis of bacterial ribosome profiling data |
title_sort | hribo: high-throughput analysis of bacterial ribosome profiling data |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8337001/ https://www.ncbi.nlm.nih.gov/pubmed/33175953 http://dx.doi.org/10.1093/bioinformatics/btaa959 |
work_keys_str_mv | AT gelhausenrick hribohighthroughputanalysisofbacterialribosomeprofilingdata AT svenssonsarahl hribohighthroughputanalysisofbacterialribosomeprofilingdata AT froschauerkathrin hribohighthroughputanalysisofbacterialribosomeprofilingdata AT heylflorian hribohighthroughputanalysisofbacterialribosomeprofilingdata AT hadjeraslydia hribohighthroughputanalysisofbacterialribosomeprofilingdata AT sharmacynthiam hribohighthroughputanalysisofbacterialribosomeprofilingdata AT eggenhoferflorian hribohighthroughputanalysisofbacterialribosomeprofilingdata AT backofenrolf hribohighthroughputanalysisofbacterialribosomeprofilingdata |