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NGScloud2: optimized bioinformatic analysis using Amazon Web Services

BACKGROUND: NGScloud was a bioinformatic system developed to perform de novo RNAseq analysis of non-model species by exploiting the cloud computing capabilities of Amazon Web Services. The rapid changes undergone in the way this cloud computing service operates, along with the continuous release of...

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Autores principales: Mora-Márquez, Fernando, Vázquez-Poletti, José Luis, López de Heredia, Unai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8054753/
https://www.ncbi.nlm.nih.gov/pubmed/33959420
http://dx.doi.org/10.7717/peerj.11237
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author Mora-Márquez, Fernando
Vázquez-Poletti, José Luis
López de Heredia, Unai
author_facet Mora-Márquez, Fernando
Vázquez-Poletti, José Luis
López de Heredia, Unai
author_sort Mora-Márquez, Fernando
collection PubMed
description BACKGROUND: NGScloud was a bioinformatic system developed to perform de novo RNAseq analysis of non-model species by exploiting the cloud computing capabilities of Amazon Web Services. The rapid changes undergone in the way this cloud computing service operates, along with the continuous release of novel bioinformatic applications to analyze next generation sequencing data, have made the software obsolete. NGScloud2 is an enhanced and expanded version of NGScloud that permits the access to ad hoc cloud computing infrastructure, scaled according to the complexity of each experiment. METHODS: NGScloud2 presents major technical improvements, such as the possibility of running spot instances and the most updated AWS instances types, that can lead to significant cost savings. As compared to its initial implementation, this improved version updates and includes common applications for de novo RNAseq analysis, and incorporates tools to operate workflows of bioinformatic analysis of reference-based RNAseq, RADseq and functional annotation. NGScloud2 optimizes the access to Amazon’s large computing infrastructures to easily run popular bioinformatic software applications, otherwise inaccessible to non-specialized users lacking suitable hardware infrastructures. RESULTS: The correct performance of the pipelines for de novo RNAseq, reference-based RNAseq, RADseq and functional annotation was tested with real experimental data, providing workflow performance estimates and tips to make optimal use of NGScloud2. Further, we provide a qualitative comparison of NGScloud2 vs. the Galaxy framework. NGScloud2 code, instructions for software installation and use are available at https://github.com/GGFHF/NGScloud2. NGScloud2 includes a companion package, NGShelper that contains Python utilities to post-process the output of the pipelines for downstream analysis at https://github.com/GGFHF/NGShelper.
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spelling pubmed-80547532021-05-05 NGScloud2: optimized bioinformatic analysis using Amazon Web Services Mora-Márquez, Fernando Vázquez-Poletti, José Luis López de Heredia, Unai PeerJ Bioinformatics BACKGROUND: NGScloud was a bioinformatic system developed to perform de novo RNAseq analysis of non-model species by exploiting the cloud computing capabilities of Amazon Web Services. The rapid changes undergone in the way this cloud computing service operates, along with the continuous release of novel bioinformatic applications to analyze next generation sequencing data, have made the software obsolete. NGScloud2 is an enhanced and expanded version of NGScloud that permits the access to ad hoc cloud computing infrastructure, scaled according to the complexity of each experiment. METHODS: NGScloud2 presents major technical improvements, such as the possibility of running spot instances and the most updated AWS instances types, that can lead to significant cost savings. As compared to its initial implementation, this improved version updates and includes common applications for de novo RNAseq analysis, and incorporates tools to operate workflows of bioinformatic analysis of reference-based RNAseq, RADseq and functional annotation. NGScloud2 optimizes the access to Amazon’s large computing infrastructures to easily run popular bioinformatic software applications, otherwise inaccessible to non-specialized users lacking suitable hardware infrastructures. RESULTS: The correct performance of the pipelines for de novo RNAseq, reference-based RNAseq, RADseq and functional annotation was tested with real experimental data, providing workflow performance estimates and tips to make optimal use of NGScloud2. Further, we provide a qualitative comparison of NGScloud2 vs. the Galaxy framework. NGScloud2 code, instructions for software installation and use are available at https://github.com/GGFHF/NGScloud2. NGScloud2 includes a companion package, NGShelper that contains Python utilities to post-process the output of the pipelines for downstream analysis at https://github.com/GGFHF/NGShelper. PeerJ Inc. 2021-04-16 /pmc/articles/PMC8054753/ /pubmed/33959420 http://dx.doi.org/10.7717/peerj.11237 Text en ©2021 Mora-Márquez et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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
Mora-Márquez, Fernando
Vázquez-Poletti, José Luis
López de Heredia, Unai
NGScloud2: optimized bioinformatic analysis using Amazon Web Services
title NGScloud2: optimized bioinformatic analysis using Amazon Web Services
title_full NGScloud2: optimized bioinformatic analysis using Amazon Web Services
title_fullStr NGScloud2: optimized bioinformatic analysis using Amazon Web Services
title_full_unstemmed NGScloud2: optimized bioinformatic analysis using Amazon Web Services
title_short NGScloud2: optimized bioinformatic analysis using Amazon Web Services
title_sort ngscloud2: optimized bioinformatic analysis using amazon web services
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8054753/
https://www.ncbi.nlm.nih.gov/pubmed/33959420
http://dx.doi.org/10.7717/peerj.11237
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