The interest in investigating the biological roles of small non-coding RNAs (sncRNAs) is increasing, due to the pleiotropic effects of these molecules exert in many biological contexts. While several methods and tools are available to study microRNAs (miRNAs), only few focus on novel classes of sncRNAs, in particular PIWI-interacting RNAs (piRNAs). To overcome these limitations, we implemented iSmaRT (integrative Small RNA Tool-kit), an automated pipeline to analyze smallRNA-Seq data. Availability and Implementation: iSmaRT is a collection of bioinformatics tools and own algorithms, interconnected through a Graphical User Interface (GUI). In addition to performing comprehensive analyses on miRNAs, it implements specific computational modules to analyze piRNAs, predicting novel ones and identifying their RNA targets. A smallRNA-Seq dataset generated from brain samples of Huntington’s Disease patients was used here to illustrate iSmaRT performances, demonstrating how the pipeline can provide, in a rapid and user friendly way, a comprehensive analysis of different classes of sncRNAs. iSmaRT is freely available on the web at ftp://labmedmolge-1.unisa.it
iSmaRT: a toolkit for a comprehensive analysis of small RNA-Seq data
MEMOLI, DOMENICO;NASSA, GIOVANNI;RAVO, MARIA;RIZZO, FRANCESCA;TARALLO, ROBERTA;WEISZ, Alessandro;GIURATO, GIORGIO
2017-01-01
Abstract
The interest in investigating the biological roles of small non-coding RNAs (sncRNAs) is increasing, due to the pleiotropic effects of these molecules exert in many biological contexts. While several methods and tools are available to study microRNAs (miRNAs), only few focus on novel classes of sncRNAs, in particular PIWI-interacting RNAs (piRNAs). To overcome these limitations, we implemented iSmaRT (integrative Small RNA Tool-kit), an automated pipeline to analyze smallRNA-Seq data. Availability and Implementation: iSmaRT is a collection of bioinformatics tools and own algorithms, interconnected through a Graphical User Interface (GUI). In addition to performing comprehensive analyses on miRNAs, it implements specific computational modules to analyze piRNAs, predicting novel ones and identifying their RNA targets. A smallRNA-Seq dataset generated from brain samples of Huntington’s Disease patients was used here to illustrate iSmaRT performances, demonstrating how the pipeline can provide, in a rapid and user friendly way, a comprehensive analysis of different classes of sncRNAs. iSmaRT is freely available on the web at ftp://labmedmolge-1.unisa.itI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.