RedeR: R/Bioconductor package for representing modular structures, nested networks and multiple levels of hierarchical associations

Visualization and analysis of molecular networks are both central to systems biology. However, there still exists a large technological gap between them, especially when assessing multiple network levels or hierarchies. Here we present RedeR, an R/Bioconductor package combined with a Java core engine for representing modular networks. The functionality of RedeR is demonstrated in two different scenarios: hierarchical and modular organization in gene co-expression networks and nested structures in time-course gene expression subnetworks. Our results demonstrate RedeR as a new framework to deal with the multiple network levels that are inherent to complex biological systems. RedeR is available from http://bioconductor.org/packages/release/bioc/html/RedeR.html.

[1]  Edward M. Reingold,et al.  Graph drawing by force‐directed placement , 1991, Softw. Pract. Exp..

[2]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[3]  Michael Kaufmann,et al.  Drawing graphs: methods and models , 2001 .

[4]  Gordon K Smyth,et al.  Statistical Applications in Genetics and Molecular Biology Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments , 2011 .

[5]  Clifford A. Meyer,et al.  Genome-wide analysis of estrogen receptor binding sites , 2006, Nature Genetics.

[6]  Gábor Csárdi,et al.  The igraph software package for complex network research , 2006 .

[7]  Hidetoshi Shimodaira,et al.  Pvclust: an R package for assessing the uncertainty in hierarchical clustering , 2006, Bioinform..

[8]  Benno Schwikowski,et al.  Graph-based methods for analysing networks in cell biology , 2006, Briefings Bioinform..

[9]  Feng Luo,et al.  Modular organization of protein interaction networks , 2007, Bioinform..

[10]  Jingtai Han.  Understanding biological functions through molecular networks , 2008, Cell Research.

[11]  Akhilesh Pandey,et al.  Human Protein Reference Database and Human Proteinpedia as discovery tools for systems biology. , 2009, Methods in molecular biology.

[12]  A. Barabasi,et al.  Network medicine : a network-based approach to human disease , 2010 .

[13]  Tobias Müller,et al.  Bioinformatics Applications Note Systems Biology Bionet: an R-package for the Functional Analysis of Biological Networks , 2022 .

[14]  Trey Ideker,et al.  Cytoscape 2.8: new features for data integration and network visualization , 2010, Bioinform..

[15]  Xin Wang,et al.  Bioinformatics Applications Note Systems Biology Htsanalyzer: an R/bioconductor Package for Integrated Network Analysis of High-throughput Screens , 2022 .

[16]  Marcel J. T. Reinders,et al.  CytoscapeRPC: a plugin to create, modify and query Cytoscape networks from scripting languages , 2011, Bioinform..

[17]  R. Norel,et al.  The self-assessment trap: can we all be better than average? , 2011, Molecular systems biology.

[18]  Nolwenn Le Meur,et al.  Analyzing biological data using R: methods for graphs and networks. , 2012, Methods in molecular biology.

[19]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .