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Network analyses, such as of gene co-expression networks, metabolic networksand ecological networks have become a central approach for the systems-levelstudy of biological data. Several software packages exist for generating andanalyzing such networks, either from correlation scores or the absolute valueof a transformed score called weighted topological overlap (wTO). However,since gene regulatory processes can up- or down-regulate genes, it is of greatinterest to explicitly consider both positive and negative correlations whenconstructing a gene co-expression network. Here, we present an R package forcalculating the wTO, that, in contrast to existing packages, explicitlyaddresses the sign of the wTO values, and is thus especially valuable for theanalysis of gene regulatory networks. The package includes the calculation ofp-values (raw and adjusted) for each pairwise gene score. Our package alsoallows the calculation of networks from time series (without replicates). Sincenetworks from independent datasets (biological repeats or related studies) arenot the same due to technical and biological noise in the data, weadditionally, incorporated a novel method for calculating a consensus network(CN) from two or more networks into our R package. We compare our new wTOpackage to state of art packages and demonstrate the application of the wTO andCN functions using 3 independently derived datasets from healthy humanpre-frontal cortex samples. To showcase an example for the time seriesapplication we utilized a metagenomics data set. In this work, we developed asoftware package that allows the computation of wTO networks, CNs and avisualization tool in the R statistical environment. It is publicly availableon CRAN repositories under the GPL-2 Open Source License(https://cran.r-project.org/web/packages/wTO/).

wTO: an R package for computing weighted topological overlap and consensus networks with an integrated visualization tool