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

Authors :
La Ferlita, Alessandro
Alaimo, Salvatore
Di Bella, Sebastiano
Martorana, Emanuele
Laliotis, Georgios I.
Bertoni, Francesco
Cascione, Luciano
Tsichlis, Philip N.
Ferro, Alfredo
Bosotti, Roberta
Pulvirenti, Alfredo
Source :
BMC Bioinformatics. 6/3/2021, Vol. 22 Issue 1, p1-16. 16p.
Publication Year :
2021

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712105
Volume :
22
Issue :
1
Database :
Academic Search Index
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
150668933
Full Text :
https://doi.org/10.1186/s12859-021-04211-7