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Göteborgs universitets publikationer

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

Författare och institution:
Santhilal Subhash (Institutionen för biomedicin, avdelningen för medicinsk genetik och klinisk genetik); Chandrasekhar Kanduri (Institutionen för biomedicin, avdelningen för medicinsk genetik och klinisk genetik)
Publicerad i:
BMC bioinformatics, 17 ( 1 ) s. 365
Artikel, refereegranskad vetenskaplig
Sammanfattning (abstract):
Background: High-throughput technologies such as ChIP-sequencing, RNA-sequencing, DNA sequencing and quantitative metabolomics generate a huge volume of data. Researchers often rely on functional enrichment tools to interpret the biological significance of the affected genes from these high-throughput studies. However, currently available functional enrichment tools need to be updated frequently to adapt to new entries from the functional database repositories. Hence there is a need for a simplified tool that can perform functional enrichment analysis by using updated information directly from the source databases such as KEGG, Reactome or Gene Ontology etc. Results: In this study, we focused on designing a command-line tool called GeneSCF (Gene Set Clustering based on Functional annotations), that can predict the functionally relevant biological information for a set of genes in a real-time updated manner. It is designed to handle information from more than 4000 organisms from freely available prominent functional databases like KEGG, Reactome and Gene Ontology. We successfully employed our tool on two of published datasets to predict the biologically relevant functional information. The core features of this tool were tested on Linux machines without the need for installation of more dependencies. Conclusions: GeneSCF is more reliable compared to other enrichment tools because of its ability to use reference functional databases in real-time to perform enrichment analysis. It is an easy-to-integrate tool with other pipelines available for downstream analysis of high-throughput data. More importantly, GeneSCF can run multiple gene lists simultaneously on different organisms thereby saving time for the users. Since the tool is designed to be ready-to-use, there is no need for any complex compilation and installation procedures.
Ämne (baseras på Högskoleverkets indelning av forskningsämnen):
Biologiska vetenskaper ->
Bioinformatik och systembiologi
Gene enrichment tool, Real-time analysis, KEGG, Gene Ontology, Cancer enrichment, Pathway enrichments, Functional enrichments
Ytterligare information:
Project home page:
Postens nummer:
Posten skapad:
2016-09-13 09:14

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