Using Quascade for Virus Gene Analysis
Author Information
Author(s): Singh Dadabhai T, Trehan Rahul, Schmidt Bertil, Bretschneider Timo
Primary Institution: Genvea Biosciences
Hypothesis
Can comparative phyloinformatics effectively monitor and analyze the evolution of viruses in a distributed computing environment?
Conclusion
The study shows that Quascade can efficiently analyze virus genes and reveals geographical clustering of H5N1 viral isolates.
Supporting Evidence
- The study demonstrated the utility of a biologist-friendly high-performance computing workflow system.
- The analysis indicated a pattern of spatial clustering of H5N1 viral isolates based on geographical distribution.
- The workflows achieved linear speedups in execution time when using multiple processors.
Takeaway
This study created a computer program to help scientists understand how viruses change over time and where they come from. It found that H5N1 viruses are more similar based on where they are found than when they were discovered.
Methodology
The study used a graphical workflow system called Quascade to implement distributed workflows for phyloinformatics analysis of neuraminidase genes from H5N1 isolates and influenza viruses.
Limitations
The algorithms ML and Mr. Bayes could not be run on the existing system with the medium dataset due to resource limitations.
Participant Demographics
The core set includes samples isolated from various geographical locations, including Thailand and Bavaria, Germany.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website