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CATE, or CUDA Accelerated Testing of Evolution, is a GPU-powered software solution designed for large-scale parallelization in genomic analysis.
CATE is equipped to conduct evolutionary tests on expansive variant call (VCFs) genomic datasets in minutes, while comparable software takes days and requires significantly more computational resources.
CATE boldly claims this guarantee of speed and resource efficiency through its unique segmented file structure and its scalable algorithmic implementations. They are designed to be optimized for GPU-level parallelization with adaptability for CPU and SSD technologies.
To learn more about how you can use CATE in your workflow please read through our Wiki and if you want to know about the framework that CATE implements please read our published journal article.
CATE now comes equipped with Apollo. Apollo is a virion resolution within-host viral simulator. It utilizes our large-scale data processing innovations that power CATE to conduct robust, intricate simulations. To know more read our section on Apollo at the link below and our preprint.
We hope that CATE helps you in your genomic data analysis and solves the age-old problem of large-scale data processing being limited by time and resource availability.
CATE's GitHub repository has its complete documented source code.
Good luck and we hope you enjoy using CATE.