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CCC-GPU: a graphics processing unit (GPU)-accelerated nonlinear correlation coefficient for large-scale transcriptomic analyses
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DOI：10.1093/bioinformatics/btag068.png)
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Abstract
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Motivation Identifying meaningful patterns in complex biological data necessitates correlation coefficients capable of capturing diverse relationship types beyond simple linearity. Furthermore, efficient computational tools are crucial for handling the ever-increasing scale of biological datasets.Results We introduce CCC-GPU, a high-performance, GPU-accelerated implementation of the Clustermatch Correlation Coefficient (CCC). CCC-GPU computes correlation coefficients for mixed data types, effectively detects nonlinear relationships, and offers significant speed improvements over its predecessor.Availability and implementation The source code of CCC-GPU is openly available on GitHub (https://github.com/pivlab/ccc-gpu) and archived on Zenodo (https://doi.org/10.5281/zenodo.18310318), distributed under the BSD-2-Clause Plus Patent License.
Keywords:
nonlinear correlation
GPU acceleration
transcriptomic analysis
correlation coefficient
biological data
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