  Network analyses, such as of gene co-expression networks, metabolic networks
and ecological networks have become a central approach for the systems-level
study of biological data. Several software packages exist for generating and
analyzing such networks, either from correlation scores or the absolute value
of a transformed score called weighted topological overlap (wTO). However,
since gene regulatory processes can up- or down-regulate genes, it is of great
interest to explicitly consider both positive and negative correlations when
constructing a gene co-expression network. Here, we present an R package for
calculating the wTO, that, in contrast to existing packages, explicitly
addresses the sign of the wTO values, and is thus especially valuable for the
analysis of gene regulatory networks. The package includes the calculation of
p-values (raw and adjusted) for each pairwise gene score. Our package also
allows the calculation of networks from time series (without replicates). Since
networks from independent datasets (biological repeats or related studies) are
not the same due to technical and biological noise in the data, we
additionally, incorporated a novel method for calculating a consensus network
(CN) from two or more networks into our R package. We compare our new wTO
package to state of art packages and demonstrate the application of the wTO and
CN functions using 3 independently derived datasets from healthy human
pre-frontal cortex samples. To showcase an example for the time series
application we utilized a metagenomics data set. In this work, we developed a
software package that allows the computation of wTO networks, CNs and a
visualization tool in the R statistical environment. It is publicly available
on CRAN repositories under the GPL-2 Open Source License
(https://cran.r-project.org/web/packages/wTO/).
