Abstract
Identification of driver mutations can lead to a better understanding of the molecular mechanisms associated with cancer. This can be a first step towards developing diagnostic and prognostic markers. Various driver mutation prediction tools rely on different algorithm for prediction and hence there is little consensus in the predictions. The input and output formats vary across the tools. It has been suggested that an ensemble approach that takes into account various prediction scores might perform better. There is a need for a tool that can run multiple such tools on a dataset in a more accessible and modular manner, whose output can then be combined to select consensus drivers.
We developed wrappers for various driver mutation predictions tools using Galaxy based framework. In order to perform predictions using multiple tools on the same dataset, we also developed Galaxy based workflows to convert VCF format to tool specific formats. The tools are publicly available at: https://github.com/saketkc/galaxy_tools The workflows are available at: https://github.com/saketkc/galaxy_tools/tree/master/workflows
