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Bcheck: a wrapper tool for detecting RNase P RNA genes

BACKGROUND: Effective bioinformatics solutions are needed to tackle challenges posed by industrial-scale genome annotation. We present Bcheck, a wrapper tool which predicts RNase P RNA genes by combining the speed of pattern matching and sensitivity of covariance models. The core of Bcheck is a libr...

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Autores principales: Yusuf, Dilmurat, Marz, Manja, Stadler, Peter F, Hofacker, Ivo L
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996960/
https://www.ncbi.nlm.nih.gov/pubmed/20626900
http://dx.doi.org/10.1186/1471-2164-11-432
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author Yusuf, Dilmurat
Marz, Manja
Stadler, Peter F
Hofacker, Ivo L
author_facet Yusuf, Dilmurat
Marz, Manja
Stadler, Peter F
Hofacker, Ivo L
author_sort Yusuf, Dilmurat
collection PubMed
description BACKGROUND: Effective bioinformatics solutions are needed to tackle challenges posed by industrial-scale genome annotation. We present Bcheck, a wrapper tool which predicts RNase P RNA genes by combining the speed of pattern matching and sensitivity of covariance models. The core of Bcheck is a library of subfamily specific descriptor models and covariance models. RESULTS: Scanning all microbial genomes in GenBank identifies RNase P RNA genes in 98% of 1024 microbial chromosomal sequences within just 4 hours on single CPU. Comparing to existing annotations found in 387 of the GenBank files, Bcheck predictions have more intact structure and are automatically classified by subfamily membership. For eukaryotic chromosomes Bcheck could identify the known RNase P RNA genes in 84 out of 85 metazoan genomes and 19 out of 21 fungi genomes. Bcheck predicted 37 novel eukaryotic RNase P RNA genes, 32 of which are from fungi. Gene duplication events are observed in at least 20 metazoan organisms. Scanning of meta-genomic data from the Global Ocean Sampling Expedition, comprising over 10 million sample sequences (18 Gigabases), predicted 2909 unique genes, 98% of which fall into ancestral bacteria A type of RNase P RNA and 66% of which have no close homolog to known prokaryotic RNase P RNA. CONCLUSIONS: The combination of efficient filtering by means of a descriptor-based search and subsequent construction of a high-quality gene model by means of a covariance model provides an efficient method for the detection of RNase P RNA genes in large-scale sequencing data. Bcheck is implemented as webserver and can also be downloaded for local use from http://rna.tbi.univie.ac.at/bcheck
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spelling pubmed-29969602010-12-07 Bcheck: a wrapper tool for detecting RNase P RNA genes Yusuf, Dilmurat Marz, Manja Stadler, Peter F Hofacker, Ivo L BMC Genomics Methodology Article BACKGROUND: Effective bioinformatics solutions are needed to tackle challenges posed by industrial-scale genome annotation. We present Bcheck, a wrapper tool which predicts RNase P RNA genes by combining the speed of pattern matching and sensitivity of covariance models. The core of Bcheck is a library of subfamily specific descriptor models and covariance models. RESULTS: Scanning all microbial genomes in GenBank identifies RNase P RNA genes in 98% of 1024 microbial chromosomal sequences within just 4 hours on single CPU. Comparing to existing annotations found in 387 of the GenBank files, Bcheck predictions have more intact structure and are automatically classified by subfamily membership. For eukaryotic chromosomes Bcheck could identify the known RNase P RNA genes in 84 out of 85 metazoan genomes and 19 out of 21 fungi genomes. Bcheck predicted 37 novel eukaryotic RNase P RNA genes, 32 of which are from fungi. Gene duplication events are observed in at least 20 metazoan organisms. Scanning of meta-genomic data from the Global Ocean Sampling Expedition, comprising over 10 million sample sequences (18 Gigabases), predicted 2909 unique genes, 98% of which fall into ancestral bacteria A type of RNase P RNA and 66% of which have no close homolog to known prokaryotic RNase P RNA. CONCLUSIONS: The combination of efficient filtering by means of a descriptor-based search and subsequent construction of a high-quality gene model by means of a covariance model provides an efficient method for the detection of RNase P RNA genes in large-scale sequencing data. Bcheck is implemented as webserver and can also be downloaded for local use from http://rna.tbi.univie.ac.at/bcheck BioMed Central 2010-07-13 /pmc/articles/PMC2996960/ /pubmed/20626900 http://dx.doi.org/10.1186/1471-2164-11-432 Text en Copyright ©2010 Yusuf et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Yusuf, Dilmurat
Marz, Manja
Stadler, Peter F
Hofacker, Ivo L
Bcheck: a wrapper tool for detecting RNase P RNA genes
title Bcheck: a wrapper tool for detecting RNase P RNA genes
title_full Bcheck: a wrapper tool for detecting RNase P RNA genes
title_fullStr Bcheck: a wrapper tool for detecting RNase P RNA genes
title_full_unstemmed Bcheck: a wrapper tool for detecting RNase P RNA genes
title_short Bcheck: a wrapper tool for detecting RNase P RNA genes
title_sort bcheck: a wrapper tool for detecting rnase p rna genes
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996960/
https://www.ncbi.nlm.nih.gov/pubmed/20626900
http://dx.doi.org/10.1186/1471-2164-11-432
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