Merge pull request #29 from codeplaysoftware/add-accleom-update

Adding Accelom update and related assets.

_collections/_updates/2024-07-17-accelom-and-syclops.md

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+---
+title: "Accelom and SYCLOPS"
+date: 2024-07-17
+layout: update
+tags:
+  - accelom
+  - syclops
+---
+
+Due to significant improvements in genomic sequencing technology, it is now possible to sequence a full human genome for
+less than $1000 and receive genetic data on several molecular levels of the cell (genomic, transcriptome, protein
+expression, copy-number variations, and so on). However, in order to turn this genomic Big Data into useful insights for
+precision medicine, a systematic integrated study of a range of biological datasets is required. ACCELOM develops
+bespoke, reproducible multi-omics software pipelines that combine numerous molecular datasets from a host to investigate
+association patterns between molecular levels using unique, peer-reviewed statistical machine learning algorithms.
+
+![Image 1]({{'/static/images/updates/2024-07-17-accelom-and-syclops/image-1.webp' | absolute_url}})
+
+ACCELOM pipelines rely on the well-established GATK pipeline for performing secondary analysis, which transforms raw
+sequenced reads into analysis-ready variants. It is well known that the GATK pipeline is extremely computationally
+intensive[[1]][1] especially for large datasets (ex. Whole Genome Sequencing). To address this bottleneck, several hardware
+acceleration solutions have emerged to scale secondary analysis[[2]][2] [[3]][3]. While these solutions often improve
+time-to-insight by several orders of magnitude, they are closed and proprietary on both the software front (as
+accelerated pipelines not freely available) and hardware front (as they are tied to a specific vendor hardware).
+
+Through SYCLOPS, ACCELOM intends to collaborate with various partners in the development and validation of a SYCL-based
+library (SYCL-GAL) that will accelerate key stages of the GATK secondary analysis pipeline. Unlike contemporary
+solutions, SYCL-GAL library will be open source in nature to foster the adoption of open standards in genomics. Further,
+by relying on SYCL for cross-architecture parallelism, SYCL-GAL will also enable cross-platform acceleration of genomic
+data analysis, making it possible to deploy the same pipeline on CPUs, GPUs, and accelerators from several hardware
+vendors.
+
+[1]: https://www.intel.com/content/dam/www/public/us/en/documents/white-papers/deploying-gatk-best-practices-paper.pdf
+[2]: https://www.nvidia.com/en-us/clara/genomics/
+[3]: https://emea.illumina.com/products/by-type/informatics-products/dragen-secondary-analysis/order.html