PHISDetector: a web tool to detect diverse in silico phage-host interaction signals
Phage-microbe interactions not only are appealing systems to study coevolution but also have been increasingly emphasized due to their roles in human health, diseases, and novel therapeutic development. Meanwhile, their interactions leave diverse signals in bacterial and phage genomic sequences, defined as phage-host interaction signals (PHISs), such as sequence composition, CRISPR targeting, prophage, and protein-protein interaction signals. We infer that proper detection and integration of these diverse PHISs will allow us to predict phage-host interactions. Here, we developed PHISDetector, a novel tool to predict phage-host interactions by detecting and integrating diverse in silico PHISs and scoring the probability of phage-host interactions using machine-learning models based on PHIS features. PHISDetector is available as a one-stop web service version for general users to study individual inputs. A stand-alone software version is also provided to process massive phage contigs from virome studies. PHISDetector is freely available at http://www.microbiome-bigdata.com/PHISDetector/ and https://github.com/HIT-ImmunologyLab/PHISDector.