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CHPC - Research Computing Support for the University

In addition to deploying and operating high performance computational resources and providing advanced user support and training, CHPC serves as an expert team to broadly support the increasingly diverse research computing needs on campus. These needs include support for big data, big data movement, data analytics, security, virtual machines, Windows science application servers, protected environments for data mining and analysis of protected health information, and advanced networking. Visit our Getting Started page for more information.

Comparative genomics and signatures of social behavior in bees

Genomic Insights Through Computation

By Karen Kapheim, Kapheim Lab, Utah State University

The primary focus of research in the Kapheim Lab is understanding how social behavior evolves in bees. We take an integrative approach to finding answers to this question, and in doing so merge ecology, behavior, neuroscience, comparative genomics, and molecular biology. We conduct experiments in the field with live bees, process these in our molecular biology lab, and then analyze the sequence data using the CHPC. Examples of on-going projects include using metabarcoding to characterize the role of the microbiome in social behavior and health of bees. We have sequenced a portion of the bacterial 16s rRNA gene in DNA extracted from the guts of bees during various life stages. We are processing these sequences on the CHPC. As a side project, we are also using similar computational methods to characterize the metabarcodes sequenced from the guts of carrion flies to characterize the mammal community on a tropical island where we work. Other projects involve comparative genomics of bee genomes to look for signatures of evolutionary transitions between solitary and social lifestyles. We are also using the CHPC to analyze microRNA expression differences among bees that vary in social behavior, and in response to hormone treatments. In each of these projects, the CHPC staff and resources have been extremely valuable, as genomic data is particularly large and analyses would not be possible on desktop computers.

System Status

last update: 12/13/17 11:33 am
General Nodes
system cores % util.
ember 360/984 36.59%
kingspeak 804/828 97.1%
lonepeak 1040/1112 93.53%
Restricted Nodes
system cores % util.
ash 7156/7156 100%
apexarch Status Unavailable
ember 1092/1316 82.98%
kingspeak 7200/7312 98.47%
lonepeak 380/380 100%

Cluster Utilization

Last Updated: 12/6/17