Available from Version: 2.3
PAREsnip is a fast user-friendly multi-platform bioinformatics tool to find targets of small RNAs using the degradome. A full PDF manual for PAREsnip is available here
System requirements
Minimum: Java SE 6 / 6 Gb RAM Recommended: Java SE 6 / 16 Gb RAM
Starting PARESnip
Choose PAREsnip from the Tools menu in the Workbench. To start the tool from the command line, navigate to the Workbench installation directory and issue the command
java -jar Workbench.jar -tool paresnip
The syntax for providing inputs to the tool will be displayed.
PARESnip window
The PARESnip application after performing an analysis. 
Additional information and statistics for each of the input data sets is provided in the information area (top left box). This information includes the number of sequences and sequence length distributions. In the top-right box, shorter informational and instructional messages are provided to help guide a user through the analysis. The estimated time remaining to complete processing is also shown. Small RNA/target interactions are shown in the ‘Output’ table. The table can be sorted by clicking on a column header. The column order may be changed using drag and drop. The search box at the bottom-left can be used to search the table – partial strings are matched and case is ignored.
PARESnip menus
File menu
- Select Open to choose the input files.
- Select Save… or Save as… to save results.
- Select Reset to reinitialise PARESnip.
- ‘Close’ will close the window
Run menu
- Select Start to begin processing
- Select ‘Cancel’ to stop execution.
View menu
- Select View T-plots in VisSR to visualise the results in VisSR. A T-plot for each interaction can be displayed.
A description of the columns in the result file
Gene - the ID or description of the mRNA/transcript.
Category – Potential cleavage sites on a single transcript can be categorized according to degradome read abundance. Category 0 is the strongest signal and 4 the weakest.
Cleavage Position – the position on the transcript where cleavage has been identified.
P-Value – a score that indicates how likely the reported duplex occurred by chance.
*Fragment Abundance – the abundance for the degradome fragment (tag) indicating cleavage at that position.
*Weighted Fragment Abundance – calculated by dividing the abundance of a degradome fragment (tag) by the number of positions across all transcripts to which the tag has aligned.
*Normalized Weighted Fragment Abundance – weighted Fragment abundance/total number of fragments x 1,000,000.
Duplex – the sRNA|mRNA alignment.
Alignment Score – within the duplex, a mismatch contributes 1.0 to the score, unless it is a G-U (wobble) pair in which case it contributes 0.5 to the score. A gap in the alignment contributes a value of 1.0 to the score.
Short Read ID - the ID of the sRNA.
Short Read Abundance – the abundance of the sRNA.
Normalized Short Read Abundance – sRNA abundance/total number of sRNAs x 1,000,000.
HI,
How to get the degradomeID or degradome sequence related to a duplex result?
sincerely
Jean-Charles
Hi Jean-Charles,
Degradome fragments are exactly matched to the transcriptome and 5′-end alignment positions are recorded as well as degradome fragment abundance at that position. As only the position and fragment abundance are retained from the degradome data, there is currently no method provided by the tool to separately output degradome IDs/sequences. However, this is something we could include with our next update.
Best wishes,
Is it possible to generate T-plots from the command line? I tried to load the PARESnip results (command line) to VisSR (GUI) but i got an error: “An error occured while loading data from the file.”
And could you explain me the meaning of columns in the result file? I’m confused. It seems that the “Short Read ID” represents the ID of miRNA (I’m using miRBase miRNAs as reference), instead of degradome tags (my reads). In this case which colunm should I take as the read abundance at a certain cleavage site?
What means the “Fragment Abundance”? In my result the maxium is 2.0 . Is it normal?
Is it possible to output more intermediate results such as mapping result etc.
Hi Yuwen Zhou
You are correct in regards to the “Short Read ID”. It is indeed the identifier for the sRNA/miRNA. The “Short Read Abundance” column shows the abundance of the sRNA. For the abundance of degradome tags (Fragments), three abundance values are provided by the tool and are described below (prefixed with *).
It is not possible for the tool to show intermediate results like you suggest, nor is it possible to generate PAREsnip t-plots via the command line. Currently, only results generated by PAREsnip in GUI mode are compatible with VisSR in GUI mode. We appreciate your feedback and the additional functionality you have highlighted will be taken into account during future updates.
I have added a description of the column headings in the page above to help clarify the results.
We hope this helps. Please feel free to leave further comment if you need any more help
Best wishes,
Thank you very much !!!
Best wishes,
Very impressive guys … once I got over the same memory problems described above by John it works like a dream. Much much faster than Cleaveland3 and at a first glance, the results look a bit cleaner as well. Many thanks
Hi David,
Apologies for the delay in reply, I have been on holiday last week.
Thanks very much for the message
Please let us know if you have any other issues or questions regarding the Workbench. In addition please remember to subscribe to our RSS feeds to keep up to date with future improvements to our software.
Best Wishes,
Matt
Pingback: New degradome analysis tool – PAREsnip | Domaining.in blog
I’m getting an error while trying to deal with Degradome data (42 million lines, 35nt short reads):
“An out of memory error occurred in ExactMatcher”
Any ideas?
Ubuntu 11.04, 16G RAM
java version “1.6.0_22″
Apologies for the delay in reply. The university has been closed over the Easter break.
I have sent an email to the author of the PAREsnip tool to ask for further information on this. My first thoughts are that the data is too large to fit into memory.
I have a few questions, did you run the program from the sRNAWorkbenchStartup.jar? Or did you run the workbench directly?
How recently had you restarted your Ubuntu machine? Ubuntu has a system in place that reserves large amounts for a disk cache and this causes problems with our Java programs that attempt to detect and allocate “free” memory in advance to the virtual machine as Linux reports cached memory as being used (but will free it on request from software).
If you want to ensure the maximum amount of memory is allocated to the workbench you can configure this by hand.
Type the command (for example):
java –Xms10g –Xmx10g –jar Workbench.jar
to allocate 10Gb of RAM to the workbench. This may help with your memory problem. In addition, when I have further information from the author of the tool I will get back to you!
Is this tool animal specific or even the plants are included???kindly let me know through the email….
In principle, the tool would work on animal data provided you can acquire a degradome (which may prove difficult). Therefore PARESnip is most likely to be used for plant miRNA target prediction.