NVIDIA Clara Imaging is a computational platform that makes it easy for developers to build, manage, and deploy intelligent medical imaging workflows and instruments.
It includes capabilities for AI-Assisted Annotation, making any medical viewer AI capable. Clara Train also provides pre-trained models to kick-start AI development with techniques like Transfer Learning, Federated Learning, and AutoML.
Clara Train documentation:
Clara Train archive:
Clara Parabricks is a complete software solution for next generation sequencing, including short- and long-read applications, supporting workflows that start with basecalling and extend through tertiary analysis.
NVIDIA’s Clara Parabricks brings next generation sequencing to GPUs, accelerating an array of gold-standard tooling such as BWA-MEM, GATK4, Google’s DeepVariant, and many more. Users can achieve a 30-60x acceleration and 99.99% accuracy for variant calling when comparing against CPU-only BWA-GATK4 pipelines, meaning a single server can process up to 60 whole genomes per day. These tools can be easily integrated into current pipelines with drop-in replacement commands to quickly bring speed and data-center scale to a range of applications including germline, somatic and RNA workflows.
Clara Parabricks documentation:
Clara Parabricks archive:
The Clara Parabricks Toolkit is a technology stack of CUDA accelerated libraries and deep learning modules, C++ and Python APIs, reference applications and integrations with 3rd party applications and workflows for high performance computing, deep learning, and data analytics tools in genomics.
Use the Clara Parabricks Toolkit to develop AI-assisted workflows, to optimize mapping, aligning, and polishing for de novo genome assembly, and enhance the resolution of single cell epigenomics.
See the Clara Parabricks Developer page for more details.