- Unique identifier:
- Software type:
- Restrictions to use:
- Academic or non-commercial use
- Output data:
- The final output from GeneSCF is a table (text/tab-separated file, TSV) with list of ranked functions based on the number of hits from the user provided gene list. It also contains column with probability value (P-value) obtained by Fisher’s exact test using the contingency table and also columns containing false discovery rate (FDR) values using different multiple hypothesis correction methods.
- Programming languages:
- Perl, Shell (Bash)
- Computer skills:
- Gene Set Clustering based on Functional annotation
- Command line interface
- Input data:
- The standard input for GeneSCF is plain text document (text/plain) containing a list of genes in the form of official gene symbols.
- Operating system:
- GNU General Public License version 3.0
- R, ggplot
- Homo sapiens
- Documentation: http://genescf.kandurilab.org/documentation.php
- Chandrasekhar Kanduri <>
Due to recent changes (naming convention in FTP files) from the database KEGG (01/January/2017) and Gene Ontology (January 2017), the GeneSCF (v1.1 and v1.1-p1) file retrieval utility was unsuccessful with following issues when using update mode (--mode=update),
Example of reported issue: https://www.biostars.org/p/231071/
Other possible issues:
- Creating empty output files
- Less number of genes mapping to KEGG when using GeneSymbol as input
- Some organism from Gene Ontology was not supported
The above mentioned issues was faced by GeneSCF v1.1, v1.1-p1 users from 01/January/2017. All the problems are now rectified with new patch release GeneSCF v1.1-p2 (13/January/2017).
Thanks to all users for supporting GeneSCF and please report if there is any problem. We will continue to work on GeneSCF improvements by considering users feedback.
(Subhash and Kanduri, 2016)
GeneSCF: a real-time based functional enrichment tool with support for multiple organisms.
PMID: 27618934 DOI: 10.1186/s12859-016-1250-z
(Mondal et al., 2015)
MEG3 long noncoding RNA regulates the TGF-β pathway genes through formation of RNA-DNA triplex structures.
PMID: 26205790 DOI: 10.1038/ncomms8743
Department of Medical Genetics, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
This work was supported by the grants from the Knut and Alice Wallenberg Foundation (KAW) (Dnr KAW 2014.0057), Swedish Foundation for Strategic Research (RB13-0204), Swedish Cancer Research foundation (Cancerfonden: Kontrakt no. 150796), the Swedish Research Council (VR-M: K2014-67X-20781-07-4), Barncancerfonden (PR2014/0147), Ingabritt Och Arne Lundbergs forskningsstiftelse and LUA/ALF.
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