sRNAtoolbox: a collection of small RNA analysis tools

sRNAtoolbox is aimed to provide small RNA researchers with several useful tools including sRNA expression profiling from deep sequencing experiments and several downstream analysis tools. The center piece of sRNAtoolbox is sRNAbench, which allows the expression profiling and prediction of novel microRNAs in deep sequencing experiments. The other tools can be either launched on sRNAbench results, or independently using the appropriate file formats.

Currently the toolbox is comprised of the following methods:



Expression profiling of small RNAs and prediction of novel microRNAs from deep sequencing data

sRNAbench is principally designed for the use in model species, or at least species with an available genome assembly or annotations is fasta format. It accepts several commonly used input formats like fastq, sra, fasta or read/count. It performs the expression profiling of known microRNAs and other types of small RNAs, detects and analysis isomiRs, prepares several graphical summaries and predicts novel microRNAs both in plants and animals.


Differential expression analysis

sRNAde is a module for the detection of differentially expressed sRNA. The input is either a number of sRNAbench output folders or a user-given expression matrix. For the detection of differentially expressed RNAs it applies 3 widely used methods, edgeR, DEseq and noiseq. Apart of the output from the individual methods, it provides a consensus differential expression file. Additionally, this tool can perform cluster analysis (heatmaps), isomiR analysis and it gives a summary on the sequencing statistic of all used samples (if the input has been from sRNAbench).


Profiling and detection of novel microRNAs in non-model specie

Currently, microRNA deep sequencing data is available for many species that do not count with a proper genome assembly. In such cases, frequently simple homology based detection methods are applied. These methods can lead to false positive predictions but will also fail to detect microRNAs that are not present in the reference database (like miRBase). sRNAgFree is aimed for the prediction and expression profiling of microRNAs in non-model species. It based on the duplex properties formed by the guide and passenger strand and applies homology and learning form known binding and Drosha/Dicer processing patterns.


Blast analysis of deep sequencing reads against a local nt/nr (NCBI link) database

This tool is principally aimed for the analysis of reads that could not be mapped in sRNAbench or other profiling tools. The results could either point towards contamination sources or biological meaningful information like the presence of unexpected viral or bacterial RNA molecules.


Predict microRNA targets on user defined sets of microRNAs and 3'UTRs

Most microRNA target prediction tools are implemented as webservers on a limited number of species, or do allow only the prediction of a limited number of microRNAs and/or mRNAs. miRNAconsTargets uses two microRNA target prediction programs, miranda and TargetSpy and applies them to the user supplied sets of microRNAs and 3'UTRs. It reports both, the individual predictions and a consensus prediction. Currently, only animal microRNA targets can be predicted.


Browse the small RNA expression values in a genome context

In several small RNA research fields, the visual exploration of small RNA expression pattern in a genome context will be helpful. sRNAjBrowser allows the user to analyse the expression data in a genome context by means of a jBrowser implementation. Furthermore, this tool is connected to NGSmethDB and can therefore also display some selected methylation tracks.


Visualize differential expression as a function of read length

sRNAjBrowserDE extends on sRNAjBrowser as it: i) allows the comparison of two experimental groups, i.e. it visualizes the differential expression in a genome context and ii) it allows to visualize the expression as a function of read length. This might me particularly interesting for plant research as 24nt long and 21/22nt long reads have very different functions.


Determine over represented functional annotations in target gene set

Overrepresented functional annotations in a list of target genes might give useful hints on the functional implications of the microRNAs. sRNAfuncTerms takes a set of microRNAs as input, retrieves the target genes from the underlying database and detected overrepresented GO-terms among the target genes. Apart from the complete set of microRNAs, it tests also all microRNA modules (combinations) which allow the user to detect the microRNAs that act on the same pathways or share the same functions.



Cross-species microRNA target prediction and enrichment analysis of functional annotations.

This workflow connects directly sRNAconsTargets and sRNAfuncTerms. It allows the user to i) predict the putative target genes of a set of exogenous microRNAs and ii) determine the enriched functional annotations, i.e. which pathways or functions are enriched for the target genes.

Helper Tools

These tools are intended to help the user to either setting up a local sRNAbench database (Ensembl Parser, NCBI Parser, RNA Central Parser, genomic tRNA Parser) or to prepare input data for other sRNAtoolbox tools. If you use any of the generated data in your publication, please cite the papers given at the data retrieval page (NCBI, ENSEMBL, genomic tRNA and RNA central databases).