Research Computing enables client to speed up analysis

Customer Case Study

Andi Waltmann is a postdoc in the Infectious Diseases, Epidemiology and Ecology (IDEEL) Lab of the Institute for Global Health and Infectious Diseases (IGHID). She is investigating the molecular epidemiology of malaria, enteric pathogens and sexually-transmitted infections.

The Client

For her most recent project, Waltmann has been working with Professor Steven Meshnick to understand the effects of a commonly used antimalarial (sulfadoxine-pyrimethamine, SP) on the gut microbiome of pregnant women in Malawi. SP is not only a potent antimalarial, but also a combination antibiotic with health benefits that may extend beyond malaria prevention. The goal of the project is to gain a deeper understanding of causes and ways to address adverse pregnancy and birth outcomes in communities where pathogen burdens are high.

Using stool samples from expectant mothers in their third trimester of pregnancy until delivery, Waltmann has been profiling the composition of their gut microbiome using high-throughput sequencing. This involved several sequencing runs at the High-Throughput Sequencing Core at UNC-Chapel Hill and the generation of approximately 50 million bacterial sequence reads.

The Challenge

The analysis of this rich data set involved intensive bioinformatic pipelines that often involve long waiting times if sufficient computing power is not available to perform the analysis quickly.

The Solution

Having access to the University’s Google Cloud Platform ensured a streamlined way to perform the analysis promptly and cut the time spend waiting on jobs to finish by half.

The Results

“In particular, Jeff Roach was instrumental in getting me an account, teaching me how to navigate the platform and running jobs,” Waltmann said. “Also, it’s been so helpful being able to store tens of GB of analysis output.”