Genetic Engineering & Biotechnology News

MAY15 2017

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16 | MAY 15, 2017 | GENengnews.com | Genetic Engineering & Biotechnology News to change that with a collective AI for ge- nomic data processing and analytics named SOPHiA. "Our model takes raw NGS data di- rectly from laboratory sequencers and deliv- ers a variant report to the clinician in only a few hours," said Bernardo J. Foth, Ph.D., senior bioinformatician at Sophia Genet- ics. "SOPHiA artificial intelligence analyzes raw NGS data to obtain an accurate variant detection report for each lab independently from the technologies they use. "Some variants are fairly easy to detect, like SNPs. More difficult are variants with a string of base-pair repeats or long indels [DNA deletions or insertions] on the or- der of kilobases. Our platform uses specific modules to recognize variants that are more challenging to detect, giving clinicians a comprehensive and reliable report." SOPHiA was trained early on with data from hospital collaborations and publicly available NGS datasets and is continuously learning from experts using it. An example of the AI's remarkable ability to detect chal- lenging variants is seen in the resolution of long base-pair repeats within the gene re- sponsible for cystic fibrosis, CTFR. The CTFR gene has 11 thymine-guanine (TG) repeats followed by 7 T's. Changes in these regions can be clinically relevant and must be resolved for a proper diagnosis. SO- PHiA's algorithm identifies the noise inher- ent in the raw NGS data, which is found in both the reference genome and the variant sample, and is able to determine the CTFR sequence with 99.99% sensitivity. Accurate and automated NGS reporting is only half the battle for clinicians to direct treatment decisions. They must also be in- formed of what it means for a patient to harbor a particular variant. Sophia Genet- ics' platform helps to link gene variants with pathogenicity by sharing knowledge among the 250 institutions that are part of its com- munity. Clinical classification for gene vari- ants are assigned by users and shared within the system, giving clinicians more confidence when using sequencing data to diagnose and treat patients. Another resource to help with interpreta- tion of cancer variants is the publicly avail- able Clinical Knowledgebase (CKB) from The Jackson Laboratory (JAX). The data- base contains gene and variant descriptions, drug indication statuses, clinical trial informa- tion, treatment approaches, and efficacy evi- Big Biodata Continued from page 14 OMICS Insights Genomics & Proteomics Inherited diseases represent some of the more difficult disorders to diagnose as well as treat. Now, researchers may be getting the much-needed advances in inherited disease diagnostics. Congenica and Edico Genome re- cently announced a partnership to offer their complementary platform technolo- gies as an all-in-one, genome data-anal- ysis solution. This new endeavor is set to accelerate clinical labs' and hospitals' progression from DNA sequencing to diagnosis for inherited diseases, which currently can take months or years. The new offering combines Congenica's Sapientia TM software plat- form, which allows hospitals and labs to analyze and interpret the genome while creating comprehensive diagnostic reports to support clinical decision making, with Edico Genome's DRAGEN TM , a field-programmable gate array (FPGA)-centric platform that im- plements genome pipeline algorithms to analyze a whole genome in only 20 minutes on-site or under 10 minutes in a single cloud instance. "Sapientia is already used extensively throughout the NHS in the U.K., as well as by clinical scientists providing reports for the 100,000 Genomes Project," ex- plained Thomas Weaver, Ph.D., CEO of Congenica. "Without a diagnosis, it is difficult to select the most appropriate treatment plan for a patient or make a prognosis of what the likely outcomes may be." Edico's DRAGEN Bio-IT processor has been assessed as part of University College London's (UCL) Rapid Pediatric Sequencing Project (RaPs), a pilot aimed at evaluating the use of rapid whole- genome sequencing (WGS) for rare dis- eases in an intensive care clinical setting. "Edico shares our vision of transform- ing healthcare by developing easy-to- use, highly automated genomics analy- sis solutions. And by combining our complementary technologies, we aim to accelerate the clinician's ability to use genomics to diagnose a patients' dis- ease and make this available on a global basis," Dr. Weaver stated. Pieter van Rooyen, Ph.D., CEO of Edico Genome, added that "as genom- ics marches towards the clinic, we rec- ognize clinicians and researchers need easy to use, all-in-one solutions that en- able genomic data to be analyzed and shared quickly, easily, accurately and cost effectively. Congenica has firsthand perspective of the needs of the clinical genomics community." n Partnership Looks to Improve Genetic Disease Diagnostics Next-generation DNA sequencing (NGS) experts point out that getting valid, reproducible results depends on diligence throughout the process, including the steps before and after the actual sequencing. "Successful NGS requires correct DNA sample preparation and data analytics afterward," says Mojca Strazisar, Ph.D., head of the Genomic Service Facility in the VIB-UAntwerp Center for Molecular Neurology. "Failure at either of these steps can lead to false results." During sample preparation, Dr. St- razisar's lab "quality checks" samples to ensure reproducible results. While QC can be time and labor intensive, the Genomic Service Facility has stream- lined the process with two Fragment Analyzers™ from Advanced Analytical Technologies. These parallel capillary electrophoresis instruments leverage automation and standardized workflows to assess the size and quality of DNA fragments prior to sequencing. "Their automation means minimal hands-on time. The Fragment Analyzers also use the same protocols and con- sumables across throughput levels, so we don't need to specialize training or equipment," points out Dr. Strazisar. After sequencing, the challenge then becomes interpreting the massive outflow of data. The Genomic Service Facility compares their sequence data to the reference human genome to find genetic variants, and often does this across cohorts of hundreds or thousands of different NGS libraries. "We're producing larger and larger amounts of data, but this also increases the risk of error. The key is being able to differentiate between biologically rele- vant information and technical artifacts," says Dr. Strazisar. "We're staffed with three bioinformaticians, of which two focus solely on data analysis and inter- pretation, and we use an in-house data pipeline to provide tailor-made solutions depending on our research questions." As a result of the Genomic Service Fa- cility's investments in the front and back end, alongside its Illumina NGS and Oxford Nanopore platforms, Dr. Stra- zisar's lab can perform experiments that were impossible only a few years before. "NGS was once limited to analyzing short DNA fragments for variants and small deletions or insertions, but long- read sequencing is allowing researchers to see large structural genetic variations that were previously invisible. This has the potential to illuminate genetic fac- tors and drug targets for complex neuro- degenerative diseases which are at the core of VIB Antwerp's research." n Minimizing Failures in NGS Avere System's hybrid cloud model combines on-premises (on-prem) and cloud-computing models. Data stored on a network-attached storage (NAS) system can be localized on-prem or in the cloud, and processed with low latency, either on-prem or in a cloud-.computing environment. Transfer of data from on-prem NAS to the cloud uses "bursting," a type of read-ahead caching to transfer relevant data only when needed during processing. This kind of transfer can decrease latency.

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