NVIDIA Clara Imaging is a computational platform that makes it easy for developers to build, manage, and deploy intelligent medical imaging workflows and instruments.

NVIDIA Clara Train Application Framework

Clara Train Application Framework is a domain optimized developer application framework that includes APIs for AI-Assisted Annotation, making any medical viewer AI capable and a TensorFlow based training framework with pre-trained models to kick start AI development with techniques like Transfer Learning, Federated Learning and AutoML.

Clara Train Application Framework documentation includes:

NVIDIA Clara Deploy Application Framework

Clara Deploy Application Framework provides a container based development & deployment framework for building AI accelerated medical imaging workflows. Using Kubernetes, it enables you to define a multi-staged container based pipeline. The modular architecture allows you to use the offerings of the platform end-end or customize the workflow pipelines with bring-your-own algorithms.

Clara Deploy documentation:

Clara Deploy Early Access documentation:

Clara Deploy 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 Clara Parabricks Pipelines

Based on the Broad Institute’s Genome Analysis Toolkit (GATK), Clara Parabricks Pipelines enable GPU-accelerated GATK along with other third party tools, like Google’s DeepVariant caller. Currently, GATK v4.1 is supported and Best Practices are enabled. Starting with DNA sequencing reads, Clara Parabricks Pipelines map, align, filter and call variants for either germline or somatic variant detection. For RNA based projects, both STAR and STAR-Fusion align sequencing reads allowing for reads to be split to account for exon/intron boundaries, followed by variant calling.

Clara Parabricks Pipelines were built to optimize acceleration, accuracy and scalability. Users can achieve a 35-50X acceleration and 99.99% accuracy for variant calling when comparing against CPU-only BWA-GATK4 pipelines. It can run the full GATK4 Best Practices, and is also fully configurable. As a result, you can choose which steps, parameter settings, and versions of the pipeline to run.

Clara Parabricks documentation:

Clara Parabricks archive:

NVIDIA Clara Parabricks Toolkit

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.