Tapping NSCC’s supercomputer to support the surveillance and control of vector-borne and environment-related diseases like dengue in Singapore.
In July, the number of dengue cases in Singapore surpassed the entire total number of cases recorded in 2019. While the focus may now be on COVID-19, dengue and other mosquito-borne diseases are a recurring threat in tropical Singapore. The risk of disease outbreaks caused by vector-borne and environment-related pathogens remains high, with notable examples being diseases such as dengue, chikungunya and zika fever.
The Environmental Health Institute (EHI), a public health research laboratory under the National Environment Agency (NEA), conducts research, surveillance and evidence-based risk assessment on infectious diseases of environmental concern in Singapore. The important components of EHI’s research programmes include arbovirus surveillance, genetic profiling of vector-borne and environment-related pathogens and associated vectors to understand their spatio-temporal dynamics. Data is also useful for modelling of outbreak risk and data analytics to assess the impact of disease control strategies.
A team of researchers at EHI are utilising NSCC’s supercomputing resources to improve the efficiency and throughput of data analytics required for research and surveillance activities.
A major portion of EHI’s analyses is currently focused on generating phylogeography and evolutionary data by using the BEAST software. BEAST requires 100-400 million iterations of MCMC-chain per run, which is time and resource consuming. Therefore, in the NSCC environment, the team has the ability to enhance the speed of analysis by integrating BEAGLE libraries into beast software for effective parallelisation of processes. Using instances of BEAGLE available at NSCC, they are able to improve the speed by 3-5 times relative to BEAST software without parallelisation.
The team is also tapping NSCC’sresources for next generation sequencing (NGS) high throughput data analysis by parallelising genome alignment tools and are planning to use NGS pipelines to tap on various NSCC resources such as singularity and conda environments. “With the resources at NSCC, the current project expects to scale up the resolution and efficiency of genetic data analyses that would benefit the evidencebased approaches to maintain high public health standards in Singapore,” said Chanditha, the lead of this project.
To find out more about the NSCC’s HPC resources and how you can tap on them, please contact [email protected].
NSCC NewsBytes November 2020
Other Case Studies
Increasing the effectiveness of antibiotics by analysing antibiotic resistance using supercomputers
Researchers from NTU are utilising NSCC’s supercomputing resources to understand the permeation of antibiotics in order to design new novel antibiotics. Antibiotic resistance is...
Using Machine Learning to identify and improve protein-ligand binding affinity predictions
Researchers from NTU are utilising NSCC’s supercomputing resources to improve the performance of learning models in molecular data analysis. AI is expected to play an...
A quieter way to fly – Reducing jet engine noise through HPC research
Researchers from NUS are harnessing the power of supercomputing to understand the mechanism of noise generated by jet engines to reduce the impact of noise emission on the...