GeneSCF statistics

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Citations per year

Number of citations per year for the bioinformatics software tool GeneSCF
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Tool usage distribution map

This map represents all the scientific publications referring to GeneSCF per scientific context
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Associated diseases

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Popular tool citations

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GeneSCF specifications

Information


Unique identifier OMICS_10275
Name GeneSCF
Alternative name Gene Set Clustering based on Functional annotation
Software type Package/Module
Interface Command line interface
Restrictions to use Academic or non-commercial use
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.
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.
Operating system Unix/Linux
Programming languages Perl, Shell (Bash)
License GNU General Public License version 3.0
Computer skills Advanced
Version 1.1
Stability Stable
Requirements
R, ggplot
Maintained Yes

Taxon


  • Primates
    • Homo sapiens

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Versioning


No version available

Documentation


Maintainer


  • person_outline Chandrasekhar Kanduri

Publications for Gene Set Clustering based on Functional annotation

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GeneSCF: a real-time based functional enrichment tool with support for multiple organisms.

2016 BMC Bioinformatics
PMCID: 5020511
PMID: 27618934
DOI: 10.1186/s12859-016-1250-z

GeneSCF citation

library_books

Global DNA methylation profiling reveals new insights into epigenetically deregulated protein coding and long noncoding RNAs in CLL

2016
Clin Epigenetics
PMCID: 5062931
PMID: 27777635
DOI: 10.1186/s13148-016-0274-6

[…] The pathway enrichment analysis and cancer enrichment analysis on cllDMGs was carried out with the help of a command line functional enrichment tool called GeneSCF v1.1 (Gene Set Clustering based on Functional annotation) [, ]. We used GeneSCF with parameters, two different database KEGG pathways and NCG (Network of cancer Genes 4.0) [], Ensembl GRCh37.7 […]


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GeneSCF institution(s)
Department of Medical Genetics, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
GeneSCF funding source(s)
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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