Category Archives: Customer success

“Easy-to-Use” SNP & Variation Suite Assists John Curtin, PhD in Uncovering Genetic Associations for Asthma and Allergies

Dr. John Curtin is a Lecturer in Functional Genomics at the University of Manchester where he works with a large team studying the development of asthma in a birth cohort. This group has received data on study subjects periodically for over a decade including before birth. Given how much data there is, data management is a big deal to Dr…. Read more »

Agrigenomic Researcher at U.C. Davis, Gonzalo Rincon, DVM, and Colleagues Publish 14 Articles and Obtain 2 Patents Using SVS

Editor’s Note: This case study was written while Dr. Gonzalo Rincon was with the University of California, Davis. Dr. Rincon is now working as a Principal Investigator in Animal Genetics at Zoetis. Gonzalo Rincon, DVM is a Project Scientist in the Medrano Lab, part of the Department of Animal Science, at the University of California, Davis. While the lab works… Read more »

Researcher Uses SVS for Pharmacogenetic Associations for 10 Years

Dr. Julia Pinsonneault is a Research Scientist at The Ohio State University where she works to find biomarkers that guide effective treatment. Published recently in Neuropsychopharmacology, Julia has found success using SVS to find novel associations that move her research forward. Usually managing 3-5 research projects at a time from various cohorts, she found time in her busy schedule this… Read more »

Can SVS Help Plant Genetics Researchers too? You betcha!

Dr. Raman Babu is a Maize Molecular Breeder at the International Maize and Wheat Improvement Center (CIMMYT). Like his counterparts conducting human genetic research, Babu used to rely entirely on free, open-source tools to complete his work. Frustrated with continual crashes and technology that was developed in the pre-SNP era, Babu switched to SNP & Variation Suite (SVS) almost a… Read more »

Wondering what SVS can do for a PhD student? Just ask Sander.

Sander van der Laan is like many PhD students in the genomic analysis space. He has a lot of data and a lot of ideas for how to analyze it. His professor wants results. He’s the only one doing genetics (everyone else in his department is doing proteomics), so there’s always too much to do. And he finds command-line tools… Read more »