Available from Version 4.5

PAREsnip2 is a user friendly, cross-platform software tool for predicting small RNA targets from degradome sequencing data. Not only is PAREsnip2 able to process large sequencing data sets very efficiently, it is able to perform analysis using a user configurable set of targeting rules.

We also have a T-plot creation tool that you can find here.

A user manual for PAREsnip2 can be found here and a set of tutorial data can be downloaded from here.

System Requirements

At the time of writing Java 9 is not yet supported

Minimum: Java SE 8 and 6GB RAM

Recommended: Java SE 8 and 16GB RAM

PAREsnip2 has been tested on Windows (7 and 10), Linux (Ubuntu 16.04) and MacOS (10.13). If you have any issues with the execution of PAREsnip, please let us know by email or in the comments.

Running PAREsnip2

You can perform the analysis using PAREsnip2 either through the user friendly graphical user interface (GUI) or through the command-line.

GUI Analysis

PAREsnip2 is a tool within the UEA sRNA Workbench. In order to run the sRNA Workbench in GUI mode, simply download the latest version from here and extract all the files from your downloaded zip archive to a new directory and then launch the Workbench.jar.

Next, click Open/Close menu -> Pre-configured Workflows -> Create PAREsnip2 Workflow. To load the input data, double click on the ‘Data Input’ node. The first step is to add your short-read sequence files. Add one or more Small RNA and Degradome replicates by clicking on ‘Add Files’. One you have finished, click ‘Next’.

You now must input the reference sequence data. Select whether you want to use a transcriptome file or a GFF3 file and corresponding genome. Once you have made the selection you can choose to align the small RNA sequences to the genome (if provided). Add the sequence data by using the ‘Add File’ button and then click ‘Next’ to continue.

Once you have finished inputting the sequence data you will be asked to select the analysis configuration.

You may click on the ‘Default Flexible’ or ‘Default Stringent’ buttons to load the default configurations. Optionally, you can save the configuration by clicking ‘Save Parameters’. Once you have finished, click on the ‘Finish’ button.

The ‘Data Input’ node will now turn blue indicating that it is ready.

Double click on the ‘Targeting Rules’ node and here you can set the chosen rules to be used during the analysis. A description of these rules can be found here or in the user manual. Optionally, you may select to the use default Fahlgren and Carrington rules or the Allen et al. rules by clicking on the ‘Carrington Rules’ or ‘Allen Rules’ button, respectively. Optionally, you can save the selected targeting rules by clicking ‘Save Rules’.

Once you have finished, click ‘Next’, and you will be provided with the option to choose permissible and non-permissible mismatch positions.

Both nodes will now be turned blue indicating that they are ready.

To start the analysis, click on ‘Open/Close Menu’ and then finally on ‘Begin Workflow’.

Command-line analysis

In order to execute the sRNA Workbench and PAREsnip2 from the command line, navigate to the directory that you extracted the sRNA Workbench files to. Open a console window and type the following command:

java -jar Workbench.jar -tool paresnip2

If no options are entered, the usage instructions will be printed to the command line. An example of a complete instruction is given below:


java [-XmxNg] -jar /path/to/Workbench.jar -tool paresnip2 -parameters /path/to/parameter/file -targeting_rules /path/to/targeting_rules/file -srna_files /path/to/srna/file1 [/path/to/srna/file2] [...] -pare_files /path/to/pare/file1 [/path/to/pare/file2] [...] -reference /path/to/reference/file -output_dir /path/to/output/directory [-genome /path/to/genome/file] [-gff3 /path/to/gff3/file]


 -XmxNg (optional but recommended) gives N GB of memory to the Workbench process

Note: parameters in square brackets are optional (but the [] must be removed if you use them). However, if using GFF and genome as reference then the –gff3 flag should provide the gff3 file and the –reference flag should provide the genome file.

Default parameter files that can be used or edited are found in the default parameters directory of the Workbench.

A suite of tools for analysing micro RNA and other small RNA data from High-Throughput Sequencing devices