SUMMARY: The discovery of differential gene-gene correlations across phenotypical groups can help identify the activation/deactivation of critical biological processes underlying specific conditions. The presented R package, provided with a count and design matrix, extract networks of group-specific interactions that can be interactively explored through a shiny user-friendly interface. For each gene-gene link, differential statistical significance is provided through robust linear regression with an interaction term. AVAILABILITY AND IMPLEMENTATION: DEGGs is implemented in R and available on GitHub at https://github.com/elisabettasciacca/DEGGs. The package is also under submission on Bioconductor.

Rise in population aging as well as diffusion of chronic diseases and health consciousness require constant monitoring of health conditions but also lead to increasing costs for the governments. Body Area Networks represent the next frontier in health care and are envisaged as the natural choice to provide detailed and updated information on health status to prevent health risks and diseases. However if, on the one hand, a large research effort has been devoted so far to the investigation of BAN communications on and around the body, on the other hand intra-BAN communications are still a scarcely explored area because of the difficulties and risks in successfully propagating signals inside the body where RF waves cannot be employed. In this paper we propose to use ultrasonic waves for intra-BANs and we investigate on the feasibility of supporting multihopping among different intra-body devices which communicate with a gateway node in charge of transmitting health information to a remote medical center. We discuss system implementation using Universal Software Radio Peripheral (USRP) nodes and test the feasibility of multihop transmissions across a body phantom enhanced with organic tissues. Our analysis shows that multihop transmission is feasible and can be effectively employed to support communications in next-generation E-Health applications.