NGScloud: RNA-seq analysis of non-model species using cloud computing

Mora‐Márquez, Fernando; Vázquez-Poletti, José Luis; Heredia, Unai López de

doi:10.1093/bioinformatics/bty363

Cited by 6 publications

(8 citation statements)

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“…For this purpose, several pipelines have been developed for the analysis of gene expression from RNA-Seq data. Relevant examples include: ArrayExpressHTS ( https://www.bioconductor.org/packages/release/bioc/html/ArrayExpressHTS.html ), BioJupies [ 5 ], BioWardrobe [ 6 ], DEWE [ 7 ], easyRNASeq [ 8 ], ExpressionPlot [ 9 ], FX [ 10 ], GENE-counter [ 11 ], GeneProf [ 12 ], Grape RNA-Seq [ 13 ], MAP-RSeq [ 14 ], NGScloud [ 15 , 16 ], RAP [ 17 ], RobiNA [ 18 ], RSEQREP [ 19 ], RSEQtools [ 20 ], RseqFlow [ 21 ], S-MART [ 22 ], TCW [ 23 ], TRAPLINE [ 24 ] and wapRNA [ 25 ]. In addition, other pipelines have been developed for the analysis of different ncRNA classes: DSAP [ 26 ], miRanalyzer [ 27 ], miRExpress [ 28 ], miRNAkey [ 29 ], iMir [ 30 ], CAP-miRSeq [ 31 ], mirTools 2.0 [ 32 ], sRNAtoolbox [ 33 ], miRDeep 2 [ 34 ], and MapMi [ 35 ] for microRNAs (miRNAs); piPipes [ 36 ], PILFER [ 37 ], piRNAPredictor [ 38 ] and PIANO [ 39 ] for piwi-associated RNAs (piRNAs); and UClncR [ 40 ] for long non-coding RNAs (lncRNAs).…”

Section: Introductionmentioning

confidence: 99%

RNAdetector: a free user-friendly stand-alone and cloud-based system for RNA-Seq data analysis

et al. 2021

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Background RNA-Seq is a well-established technology extensively used for transcriptome profiling, allowing the analysis of coding and non-coding RNA molecules. However, this technology produces a vast amount of data requiring sophisticated computational approaches for their analysis than other traditional technologies such as Real-Time PCR or microarrays, strongly discouraging non-expert users. For this reason, dozens of pipelines have been deployed for the analysis of RNA-Seq data. Although interesting, these present several limitations and their usage require a technical background, which may be uncommon in small research laboratories. Therefore, the application of these technologies in such contexts is still limited and causes a clear bottleneck in knowledge advancement. Results Motivated by these considerations, we have developed RNAdetector, a new free cross-platform and user-friendly RNA-Seq data analysis software that can be used locally or in cloud environments through an easy-to-use Graphical User Interface allowing the analysis of coding and non-coding RNAs from RNA-Seq datasets of any sequenced biological species. Conclusions RNAdetector is a new software that fills an essential gap between the needs of biomedical and research labs to process RNA-Seq data and their common lack of technical background in performing such analysis, which usually relies on outsourcing such steps to third party bioinformatics facilities or using expensive commercial software.

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Section: Introductionmentioning

confidence: 99%

RNAdetector: a free user-friendly stand-alone and cloud-based system for RNA-Seq data analysis

et al. 2021

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“…Moreover, the informatic system developed in NGScloud2 is flexible enough to allow for further incorporation of new software applications in the future. NGScloud2 has proved its operability for RNAseq, RADseq and functional annotation analysis, but it is important to select the optimal application for each workflow step according to the specific type of data to analyze (Conesa et al, 2016;López de Heredia & Vázquez-Poletti, 2016) and the most cost-efficient instance to run each application (Mora-Márquez, Vázquez-Poletti & López de Heredia, 2018). Indeed, the instance type to use will depend on the hardware requirements of the bioinformatics software.…”

Section: Discussionmentioning

confidence: 99%

“…Here we present NGScloud2, a new version of the NGScloud software (Mora-Márquez, Vázquez-Poletti & López de Heredia, 2018). NGScloud was developed as a bioinformatics system to perform de novo RNA sequencing (RNAseq) analysis of non-model species.…”

Section: Introductionmentioning

confidence: 99%

NGScloud2: optimized bioinformatic analysis using Amazon Web Services

Mora‐Márquez

Vázquez-Poletti

Heredia

2021

PeerJ

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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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“…TOA presents some advantages in comparison to other general‐purpose existing solutions. TOA is available for free and can be run on four environments: (a) as an standalone version on a local Linux or Mac OS X computer; and (b) on the Amazon Web Services cloud version implemented in the software NGScloud2 (Mora‐Márquez et al., 2018; https://github.com/GGFHF/NGScloud2); (c) on high performance computing facilities using the console‐mode version; and (d) on Docker Hub, as a Docker image. TOA presents automated easy installation of the software and dependencies in all cases.…”

Section: Discussionmentioning

confidence: 99%

“…TOA has also been included in NGScloud2 (Mora‐Márquez et al., 2018). NGScloud2 is a system designed to perform the bioinformatic analysis of RNA‐seq experiments using the Amazon Web Services cloud available at https://github.com/GGFHF/NGScloud2.…”

Section: Methodsmentioning

confidence: 99%

TOA: A software package for automated functional annotation in non‐model plant species

Mora‐Márquez

Chano

Vázquez-Poletti

et al. 2020

Molecular Ecology Resources

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The increase of sequencing capacity provided by high‐throughput platforms has made it possible to routinely obtain large sets of genomic and transcriptomic sequences from model and non‐model organisms. Subsequent genomic analysis and gene discovery in next‐generation sequencing experiments are, however, bottlenecked by functional annotation. One common way to perform functional annotation of sets of sequences obtained from next‐generation sequencing experiments, is by searching for homologous sequences and accessing the related functional information deposited in genomic databases. Functional annotation is especially challenging for non‐model organisms, like many plant species. In such cases, existing free and commercial general‐purpose applications may not offer complete and accurate results. We present TOA (Taxonomy‐oriented annotation), a Python‐based user‐friendly open source application designed to establish functional annotation pipelines geared towards non‐model plant species that can run in Linux/Mac computers, HPCs and cloud servers. TOA performs homology searches against proteins stored in the PLAZA databases, NCBI RefSeq Plant, Nucleotide Database and Non‐Redundant Protein Sequence Database, and outputs functional information from several ontology systems: Gene Ontology, InterPro, EC, KEGG, Mapman and MetaCyc. The software performance was validated by comparing the runtimes, total number of annotated sequences and accuracy of the functional information obtained for several plant benchmark data sets with TOA and other functional annotation solutions. TOA outperformed the other software in terms of number of annotated sequences and accuracy of the annotation and constitutes a good alternative to improve functional annotation in plants. TOA is especially recommended for gymnosperms or for low quality sequence data sets of non‐model plants.

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NGScloud: RNA-seq analysis of non-model species using cloud computing

Abstract: NGScloud is freely available at https://github.com/GGFHF/NGScloud/. A manual detailing installation and how-to-use instructions is available with the distribution.

Cited by 6 publications

References 14 publications

RNAdetector: a free user-friendly stand-alone and cloud-based system for RNA-Seq data analysis

RNAdetector: a free user-friendly stand-alone and cloud-based system for RNA-Seq data analysis

NGScloud2: optimized bioinformatic analysis using Amazon Web Services

TOA: A software package for automated functional annotation in non‐model plant species

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