Complex diseases such as cancer or obesity are thought to be caused by abnormalities in multiple genes and cannot be derived to one specific location in the genome. It has been shown that identification of disease associated genes can be made through looking at interaction patterns in a protein‐protein interaction network, where the disease associated genes are represented in clusters, or disease modules. There are several algorithms developed to infer these disease modules, but studies have shown that the reliability of the results increase if multiple algorithms are used and a consensus module is derived from them. MODifieR is an R package developed to combine the results of multiple disease module inferring algorithms and has proven to provide a stable result. To increase usability of the R package and make it available not only for users with programmatic skills, MODifieR Web was developed as a web based tool with a graphical user interface. The tool was built using Angular and .NET core, invoking the MODifieR R package in the backend. The interface requires input in the form of an expression matrix and a probe map from the user, easily uploadable in a drag‐and‐drop interface. It gives the user the possibility to analyze data using seven different algorithms and provide results as gene lists and visualizes the consensus module in a network image. MODifieR Web is a first version of an application that is a novel contribution to the existing tools for identification of disease modules, although in need of further improvements to be able to serve a greater pool of users in a more effective way. The tool is available to try out at http://transbioinfo.liu.se/modifier#/home and the source code is released as an open‐source project in Github (https://github.com/emmape/MODifieRProject).