NetWalker: a contextual network analysis tool for functional genomics

Abstract

BackgroundFunctional analyses of genomic data within the context of a priori biomolecular networks can give valuable mechanistic insights. However, such analyses are not a trivial task, owing to the complexity of biological networks and lack of computational methods for their effective integration with experimental data.ResultsWe developed a software application suite, NetWalker, as a one-stop platform featuring a number of novel holistic (i.e. assesses the whole data distribution without requiring data cutoffs) data integration and analysis methods for network-based comparative interpretations of genome-scale data. The central analysis components, NetWalk and FunWalk, are novel random walk-based network analysis methods that provide unique analysis capabilities to assess the entire data distributions together with network connectivity to prioritize molecular and functional networks, respectively, most highlighted in the supplied data. Extensive inter-operability between the analysis components and with external applications, including R, adds to the flexibility of data analyses. Here, we present a detailed computational analysis of our microarray gene expression data from MCF7 cells treated with lethal and sublethal doses of doxorubicin.ConclusionNetWalker, a detailed step-by-step tutorial containing the analyses presented in this paper and a manual are available at the web site http://netwalkersuite.org.

HER2-mTOR signaling–driven breast cancer cells require ER-associated degradation to survive

“…To identify molecular networks that are induced in HER2 + breast cancers, we undertook a regression-coupled network analysis, wherein we used the t EXP , t CN , and other values calculated as described above (and further detailed in Materials and Methods) to score molecular pathways using our previously developed algorithm NetWalk (25,26). Our analyses revealed several signaling and metabolic pathways that are overexpressed in HER2 + breast cancers, with variable reproducibility in the four data sets ( Fig.…”

Systems biology approaches to study the molecular effects of caloric restriction and polyphenols on aging processes

“…Following a version of the seeded approach to network analysis, a network was then build using the signature genes as seeds with the NetWalker tool (Komurov et al 2012) in combination with the BioGrid PPI network for mus musculus (rel. 3.2.121).…”

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“…To test if CR-high and CR-low genes in different cancers are commonly associated with pro-or antitumorigenic pathways, we performed a pathway-level analysis of CNV-RNA correlations of commonly amplified genes using our previously developed network-based data analysis method, NetWalk [11,12], in breast (BRCA), brain (GBM), lung (LUAD) and skin (melanoma, SKCM)…”

“…Pathway analyses were conducted in NetWalker [11] using the CNV-mRNA correlation values for NetWalk scoring. Briefly, CNV-mRNA correlation values, where CR-high genes were defined as those having correlation r-values of > 0.4, were transformed by substracting 0.4 (f(x) = x -0.4), so that CR-high genes now have positive values and CR-low genes have negative values (for more intuitive separation of CR-high and CR-low genes/ pathways).…”