학술논문
HPC-REDItools: a novel HPC-aware tool for improved large scale RNA-editing analysis
Document Type
Academic Journal
Author
Source
BMC Bioinformatics. August 21, 2020, Vol. 21 Issue Suppl 10
Subject
Language
English
ISSN
1471-2105
Abstract
Author(s): Tiziano Flati[sup.1], Silvia Gioiosa[sup.1], Nicola Spallanzani[sup.1], Ilario Tagliaferri[sup.1], Maria Angela Diroma[sup.2], Graziano Pesole[sup.2,3], Giovanni Chillemi[sup.2,4], Ernesto Picardi[sup.2,3] and Tiziana Castrignanò[sup.5] Background Advances in next generation sequencing (NGS) technologies have [...]
Background RNA editing is a widespread co-/post-transcriptional mechanism that alters primary RNA sequences through the modification of specific nucleotides and it can increase both the transcriptome and proteome diversity. The automatic detection of RNA-editing from RNA-seq data is computational intensive and limited to small data sets, thus preventing a reliable genome-wide characterisation of such process. Results In this work we introduce HPC-REDItools, an upgraded tool for accurate RNA-editing events discovery from large dataset repositories. Availability: https://github.com/BioinfoUNIBA/REDItools2. Conclusions HPC-REDItools is dramatically faster than the previous version, REDItools, enabling big-data analysis by means of a MPI-based implementation and scaling almost linearly with the number of available cores. Keywords: RNA-editing, High Performance Computing, REDItools, Next Generation Sequencing, Sequence Analysis, Bioinformatics pipeline
Background RNA editing is a widespread co-/post-transcriptional mechanism that alters primary RNA sequences through the modification of specific nucleotides and it can increase both the transcriptome and proteome diversity. The automatic detection of RNA-editing from RNA-seq data is computational intensive and limited to small data sets, thus preventing a reliable genome-wide characterisation of such process. Results In this work we introduce HPC-REDItools, an upgraded tool for accurate RNA-editing events discovery from large dataset repositories. Availability: https://github.com/BioinfoUNIBA/REDItools2. Conclusions HPC-REDItools is dramatically faster than the previous version, REDItools, enabling big-data analysis by means of a MPI-based implementation and scaling almost linearly with the number of available cores. Keywords: RNA-editing, High Performance Computing, REDItools, Next Generation Sequencing, Sequence Analysis, Bioinformatics pipeline