Single cell analysis of DNA and RNA is an important method that allows researchers to characterize cell populations with increased resolution.
Single cell analysis of DNA and RNA is an important method that allows researchers to characterize cell populations with increased resolution.
“Combining single-cell data with complementary datasets can lead to exciting discoveries and new insights; AI, specifically machine learning (ML), is fast becoming the gold standard used to perform important tasks like dimensionality reduction and unsupervised clustering.” Emily So, Solutions Scientist at Code Ocean
However, the advantages of working on the single cell level come at a price: growing data sets require computing power that computational researchers might not have at their disposal and the complexities of setting up stable analysis pipelines can limit adoption.
To overcome these challenges three critical components are needed:
In our webinar Accelerating Single-Cell Genomics Discovery with AI, NVIDIA, and Code Ocean Emily So, Solutions Scientist at Code Ocean, discusses how combining AI/ML algorithms with NVIDIA-powered GPU acceleration in the flexible and user-friendly Code Ocean Compute Capsules helps computational researchers scale and speed up single-cell analysis.
To illustrate Emily presents two Compute Capsules:
The RAPIDS GPU Capsule contains example notebooks that demonstrate how to use RAPIDS for GPU-accelerated analysis of single-cell sequencing data. The presentation:
For any questions about GPU acceleration, the RAPIDS and ATACWorks Capsules or about Compute Capsules in general, please book a demo.