Clara Genomics was created to address the growing size and complexity of genomics sequencing & analysis with accelerated and intelligent computing.

Clara Genomics Analysis SDK is now available under Open Source terms to provide developers free and open access, please click below to access the release through GitHub.This release includes:

  • GPU accelerated implementation of the Racon consensus module for de novo genome assembly.
  • This open source release adds the cudaAligner module for accelerated alignment, including Ukkonen’s algorithm and Myer’s bit algorithm


The field of Genomics has several transformative trends that put computing at the forefront of progress: increasing instrument throughput, AI enabled analysis applications and reduction in cost of sequencing to study large populations.

NVIDIA’s GPU Accelerated Computing platform enables real-time genomics workflows with high performance computing, deep learning and analytics on a single architecture that lives on the edge in the sequencer to the datacenter and every public cloud.

A high-level workflow from sample prep to final analysis that starts with isolating the DNA of an organism. This isolated sample is then loaded on a sequencing instruments, where embedded GPUs are used to accelerate primary analysis and enable next-generation base calling using deep neural networks (DNNs).

Secondary analysis or sequence analysis uses NVIDIA GPU computing for the Genome Analysis Toolkit (GATK), DNN-based variant calling, and de novo genome assembly.

Our first release of Clara Genomics SDK will be focused on de novo assembly of long read sequencing from Oxford Nanopore and Pacific Biosciences, reducing analysis time from days to hours. The initial release includes GPU accelerated libraries and GPU accelerated applications.


Clara Genomics Technology Stack


Clara Genomics Technology Stack includes CUDA accelerated software system libraries that form the foundation of GPU computing.

  • CUDA Mapper - CUDA based library enabling algorithms for overlapping sequencing reads.
  • CUDA Aligner - CUDA accelerated library including algorithms for aligning sequencing reads, used for genome assembly applications such as Racon and for variant calling.
  • CUDA POA - CUDA library for accelerated partial order alignment, used for genome assembly polishing with applications such as Racon.

These system libraries form the compute foundation and enable the GPU acceleration of the following applications:

  • Racon Polisher - An extension of the open source Racon consensus module for genome assembly that utilizes cudaPoa for accelerated partial order alignment.
  • Racon Aligner and Mapper - Will be available in upcoming releases.

Racon project: https://github.com/isovic/racon
isovic/racon: Ultrafast consensus module for raw de novo genome assembly of long uncorrected reads. http://genome.cshlp.org/content/early/2017/01/18/gr.214270.116

Website: http://biorxiv.org/content/early/2016/08/05/068122


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Success Stories (Click logos to learn more)






Oxford Nanopore

Oxford Nanopore Technologies is shipping a PromethION with 48 flowcells, affectionately known as P48 by those in the nanopore community. The P48 has demonstrated an output of 7.3 trillion DNA bases of data using all 48 flow cells at the same time in a single run. Next to it sits a computer equipped with four GV100 32GB NVIDIA GPUs which performs basecalling at a rate to keep up with that amount of data.

Learn how Oxford Nanopore has accelerated the entire Genomics Workflow on GPUs.

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Oak Ridge National Laboratory

Researchers at the US Department of Energy’s Oak Ridge National Laboratory broke the exascale barrier, achieving a peak throughput of 1.88 exaops—faster than any previously reported science application—while analyzing genomic data on the Summit supercomputer powered by NVIDIA GPUs.



Read more about Oak Ridge





Parabricks

Anyone with a hundred bucks and a saliva sample can get some intriguing genetic insights by mail-order. But using DNA for research or clinical purposes requires the whole genome and analysing that is computationally intensive. NVIDIA’s Inception partner Parabricks is shrinking the time taken for computational analysis from days to hours.


Read more about Parabricks





ThermoFisher Scientific

Low Cost, Simple, Scalable, Real Time Sequencing enabled by ThermoFischer Scientific on NVIDIA GPUs.


Read More from this GTC Presentation