generatR: expert genomic analysis at the click of a button

点击翻译按钮获取中文摘要

generatR is a spin-out from the Queen's University of Belfast (QUB) which develops easy to use applications for the analysis of genomics data that remove bottlenecks in laboratory genomics workflows. The technology for this project was developed from research in the Functional Genomics Group, led by Dr Simon McDade at the Patrick G Johnston Centre for Cancer Research (PGJCCR) at QUB, a leading UK Cancer Research Centre with deep expertise in genomics and precision medicine.The rapid progress of genomic analysis and next generation sequencing (NGS) is revolutionising biotechnology and medicine. Data generation is escalating at exponential rates and a key aim of academic, biotech, biopharma and medical researchers is to mine these ever increasing datasets for valuable therapeutic insights. For example, developing companion diagnostic tests to help identify which patients are likely to benefit from novel drugs under development for personalised medicine approaches. The available computational tools are often ill suited for rapid analysis of such datasets, both for discovery and decision making, with each new application currently requiring new analysis protocols to be designed from the ground up.To address these challenges, we have developed the generatR toolkit; a suite of software apps developed in an open source environment which enables rapid, customisable, data analysis as new customer requirements arise. These generatR apps are focused on making the data analysis workflow quicker and more efficient - removing the need for computer programming skills and empowering end-users such as biologists, medics, and researchers. Users navigate the intuitive interface, upload datasets for rapid analyses, and can quickly and easily interpret or share the results in-app or via a cloud-publishable report. This allows us to stitch together the latest tools more quickly and efficiently in response to the latest scientific advances, empowering scientists to carry out analysis and interpretation without support of a bioinformatician, expediting delivery of genomics-informed innovations. Reducing the bottleneck of skilled data scientists has the potential to revolutionise how companies engage with data; expediting the creation of new genomics-informed innovations, and accelerating the growth of the UK's life sciences industry with better, more robust, more usable data.