Small RNAs (sRNAs) constitute an important class of post-transcriptional regulators that control critical cellular processes in bacteria. While recent research has led to a dramatic increase in the discovery of bacterial sRNAs, it is generally believed that the currently identified sRNAs constitute a limited subset of the bacterial sRNA repertoire. In several cases, sRNAs belonging to a specific class are already known and the challenge is to identify additional sRNAs belonging to the same class. InvenireSRNA is an R package for learning a classification model for a given class of sRNA thus allowing for the discovery of additional sRNAs beloning to the same class. InvenireSRNA also provides a pretrained model for predicting RsmA/CsrA regulating sRNAs.
Before installing this package, make sure you have the latest version of Rstudio, R and the devtools package. You also need to have C++11 available on your machine for the algorithm to run properly. The python package Biopython is also required for running the algorithm. Finally, you will need to install the ViennaRNA package. You can install this R pacakge using the following:
library(devtools)
install_github("carltonyfakhry/InvenireSRNA")
For an introduction to InvenireSRNA, please see the Vignette for this package using the following:
browseVignettes("InvenireSRNA")
An interactive webserver providing some of the functionality as this R package is available at InvenireSRNA web server.
Carl Tony Fakhry, Prajna Kulkarni, Ping Chen, Rahul Kulkarni and Kourosh Zarringhalam (2017). "Prediction of bacterial small RNAs in the RsmA (CsrA) and ToxT pathways: a machine learning approach." BMC Genomics, 18.