The ability to detect the presence of a disease causing pathogen is the first step in formulating the treatment and containment strategy. Traditional pathogen detection methods rely upon the identification of agents that are already known to be associated with a particular clinical syndrome. The emerging field of metagenomics has the potential to revolutionize pathogen detection by allowing the simultaneous detection of all microorganisms in a clinical sample through the use of next-generation DNA sequencing. Over the last 20 years, the scientific community has designed individual DNA-based molecular diagnostics tests for most diseases of interest. Often times simple pathogen detection is not possible and scientists have to design test panels to detect different strains/types of a known disease. Every single test in this pathogen screening panel can adversely interact with each other and create inaccurate results. Hundreds of thousands of potential interactions need to be monitored, evaluated, and optimized during the panel design process. In short, the computational expertise needed to design such diagnostic tools is not always found in clinicians tasked with outbreak investigations.
The Fofanov Lab at Northern Arizona University, has designed and implemented a software application that automatically reviews the possible interactions that arise during panel creations, scores the quality of potential panels and generally helps the user design a better diagnostic panel.
This application has been widely used by researchers at NAU, but because of the Command Line Interface the application is not truly appealing to the larger biology community.
To ensure that this software is widely available to users of varying technical expertise, Dr. Fofanov and Dr. Furstenau decided to task our team with the implementation of Graphical User Interface for this application. This GUI will create a more intuitive user interface which will eliminate the challenges faced by non-technical users when using a command line based application.
The Fofanov Lab is part of The School of Informatics, Computing, and Cyber Systems (SICCS) at Northern Arizona University. The lab's primary area of research is in Bioinformatics. To learn more click here .
Compatible with Mac, Linux and Windows
Easy-to-use interface
Fast loading times
Output visualizations for analysis purposes
Ability to go back and forth between analysis stages
Intuitive navigation and smart window design
Images of various stages in the development of Primacy
Northern Arizona University
Flagstaff, AZ 86011
TuranNaimey@nau.edu