Systems biology Functional Gene Networks: R/Bioc package to generate and analyse gene networks derived from functional enrichment and clustering
نویسندگان
چکیده
Summary: Functional Gene Networks (FGNet) is an R/Bioconductor package that generates gene networks derived from the results of functional enrichment analysis (FEA) and annotation clustering. The sets of genes enriched with specific biological terms (obtained from a FEA platform) are transformed into a network by establishing links between genes based on common functional annotations and common clusters. The network provides a new view of FEA results revealing gene modules with similar functions and genes that are related to multiple functions. In addition to building the functional network, FGNet analyses the similarity between the groups of genes and provides a distance heatmap and a bipartite network of functionally overlapping genes. The application includes an interface to directly perform FEA queries using different external tools: DAVID, GeneTerm Linker, TopGO or GAGE; and a graphical interface to facilitate the use. Availability and implementation: FGNet is available in Bioconductor, including a tutorial. URL: http://bioconductor.org/packages/release/bioc/html/FGNet.html Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
منابع مشابه
Functional Gene Networks: R/Bioc package to generate and analyse gene networks derived from functional enrichment and clustering
Functional Gene Networks (FGNet) is an R/Bioconductor package that generates gene networks derived from the results of functional enrichment analysis (FEA) and annotation clustering. The sets of genes enriched with specific biological terms (obtained from a FEA platform) are transformed into a network by establishing links between genes based on common functional annotations and common clusters...
متن کاملSANTA: Quantifying the Functional Content of Molecular Networks
Linking networks of molecular interactions to cellular functions and phenotypes is a key goal in systems biology. Here, we adapt concepts of spatial statistics to assess the functional content of molecular networks. Based on the guilt-by-association principle, our approach (called SANTA) quantifies the strength of association between a gene set and a network, and functionally annotates molecula...
متن کاملGOsummaries : an R Package for Visual Functional Annotation of
Functional characterisation of gene lists using Gene Ontology (GO) enrichment analysis is a common approach in computational biology, since many analysis methods end up with a list of genes as a result. Often there can be hundreds of functional terms that are significantly associated with a single list of genes and proper interpretation of such results can be a challenging endeavour. There are ...
متن کاملIdentification of key genes and pathways involved in vitiligo vulgaris by gene network analysis
Background and Aim: Vitiligo vulgaris is an acquired, chronic skin and hair condition characterized clinically by loss of melanin, which, if untreated, is typically progressive and irreversible. The aim of the present study was to identify potential genes involved in the pathogenesis of vitiligo. Methods: One dataset of mRNA expression in patients with vitiligo (GSE65127) were obtained from ...
متن کاملGOsummaries: an R Package for Visual Functional Annotation of Experimental Data
Functional characterisation of gene lists using Gene Ontology (GO) enrichment analysis is a common approach in computational biology, since many analysis methods end up with a list of genes as a result. Often there can be hundreds of functional terms that are significantly associated with a single list of genes and proper interpretation of such results can be a challenging endeavour. There are ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015