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corseq: fast and efficient identification of favoured codons from next generation sequencing reads
BACKGROUND: Optimization of transgene expression can be achieved by designing coding sequences with the synonymous codon usage of genes which are highly expressed in the host organism. The identification of the so-called “favoured codons” generally requires the access to either the genome or the cod...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6035725/ https://www.ncbi.nlm.nih.gov/pubmed/30013827 http://dx.doi.org/10.7717/peerj.5099 |
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author | Camiolo, Salvatore Porceddu, Andrea |
author_facet | Camiolo, Salvatore Porceddu, Andrea |
author_sort | Camiolo, Salvatore |
collection | PubMed |
description | BACKGROUND: Optimization of transgene expression can be achieved by designing coding sequences with the synonymous codon usage of genes which are highly expressed in the host organism. The identification of the so-called “favoured codons” generally requires the access to either the genome or the coding sequences and the availability of expression data. RESULTS: Here we describe corseq, a fast and reliable software for detecting the favoured codons directly from RNAseq data without prior knowledge of genomic sequence or gene annotation. The presented tool allows the inference of codons that are preferentially used in highly expressed genes while estimating the transcripts abundance by a new kmer based approach. corseq is implemented in Python and runs under any operating system. The software requires the Biopython 1.65 library (or later versions) and is available under the ‘GNU General Public License version 3’ at the project webpage https://sourceforge.net/projects/corseq/files. CONCLUSION: corseq represents a faster and easy-to-use alternative for the detection of favoured codons in non model organisms. |
format | Online Article Text |
id | pubmed-6035725 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60357252018-07-16 corseq: fast and efficient identification of favoured codons from next generation sequencing reads Camiolo, Salvatore Porceddu, Andrea PeerJ Bioinformatics BACKGROUND: Optimization of transgene expression can be achieved by designing coding sequences with the synonymous codon usage of genes which are highly expressed in the host organism. The identification of the so-called “favoured codons” generally requires the access to either the genome or the coding sequences and the availability of expression data. RESULTS: Here we describe corseq, a fast and reliable software for detecting the favoured codons directly from RNAseq data without prior knowledge of genomic sequence or gene annotation. The presented tool allows the inference of codons that are preferentially used in highly expressed genes while estimating the transcripts abundance by a new kmer based approach. corseq is implemented in Python and runs under any operating system. The software requires the Biopython 1.65 library (or later versions) and is available under the ‘GNU General Public License version 3’ at the project webpage https://sourceforge.net/projects/corseq/files. CONCLUSION: corseq represents a faster and easy-to-use alternative for the detection of favoured codons in non model organisms. PeerJ Inc. 2018-07-04 /pmc/articles/PMC6035725/ /pubmed/30013827 http://dx.doi.org/10.7717/peerj.5099 Text en ©2018 Camiolo and Porceddu http://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/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Camiolo, Salvatore Porceddu, Andrea corseq: fast and efficient identification of favoured codons from next generation sequencing reads |
title | corseq: fast and efficient identification of favoured codons from next generation sequencing reads |
title_full | corseq: fast and efficient identification of favoured codons from next generation sequencing reads |
title_fullStr | corseq: fast and efficient identification of favoured codons from next generation sequencing reads |
title_full_unstemmed | corseq: fast and efficient identification of favoured codons from next generation sequencing reads |
title_short | corseq: fast and efficient identification of favoured codons from next generation sequencing reads |
title_sort | corseq: fast and efficient identification of favoured codons from next generation sequencing reads |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6035725/ https://www.ncbi.nlm.nih.gov/pubmed/30013827 http://dx.doi.org/10.7717/peerj.5099 |
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