Sebnif: self-estimation based novel lincRNA filter pipeline

Sebnif is free for academic, nonprofit, and personal use under the Boost Software License.
However, a license is required for commercial usage. Please contact the author for more inquires.

Sebnif webserver

Click here to submit your data and run sebnif on our webserver.

Download package

The latest release of sebnif is 1.3rc, Jul 2014.
Click here to download the source package (sebnif-1.3rc.tar.gz).
Please note that this is a pre-release version.

There are lots of changes/improvements in this version, including:
  1. Add Gaussian Mixture Model for STGE algorithm (requires mixtools package);
  2. Rewrite the Repeat Region Filter for a higher speed;
  3. Adjust the FRFE to use the lower expression boundary of the selected quantile;
  4. Updated annotation files and add a shell script for downloading the most latest ones from our server.
For more details, please refer to the change.log file in the package.

The stable version described/used in our paper (v1.2.2, Jan 2014) is also available for download here.


Sebnif is implemented in Perl (version 5.8 or higher) and R (version 2.10 or higher) for Linux/Unix platform.
For R, the library MASS is required.

Sebnif depends on iSeeRNA, a copy of which is included in the source package but configuration is needed.
If you do not work on x86_64 platform, you need to compile one iSeeRNA for your platform and replace
the one in the package. Please visit iSeeRNA webpage for more information.

How to run sebnif

One copy of ab initio assembled transcripts (example/HSkMC.gff.bz2, compiled by the authors) using
RNA-seq data from the ENCODE Project is available in the source package for testing purpose.

A shell script is provided to run sebnif on this dataset (for x86_64 platform):

    user@linux$ ./run_example.sh

This command will configure iSeeRNA by downloading files from our server and then run sebnif using all the
default parameters.
The result will be written into the file novel.final.gff under a newly created example/sebnif/ directory.

Note that the download procedure may take some time depending on the speed of your network.

For more information please refer to README file in the package.


When referencing, please cite "Sun K, Zhao Y, Wang H, Sun H (2014) Sebnif: An Integrated Bioinformatics
Pipeline for the Identification of Novel Large Intergenic Noncoding RNAs (lincRNAs) - Application in Human
Skeletal Muscle Cells. PLoS ONE 9(1): e84500. doi:10.1371/journal.pone.0084500"   PubMed   Full Text


For more inquiries, please contact the authors.

Last update: Aug 8, 2014