QIAGEN launches QCI Secondary Analysis, a new cloud-based secondary analysis solution for oncology and inherited disease applications that enables high-throughput data analysis with limited resource and infrastructure investment.
Next-generation sequencing (NGS) has rapidly gained popularity as a diagnostic testing approach due to its unparalleled ability to comprehensively analyze genetic information with high throughput and precision. However, small and decentralized labs face significant hurdles when it comes to adopting NGS testing. From high upfront costs associated with acquiring the necessary equipment, to the complexity of bioinformatics tools and compliance management that require specialized expertise in data analysis and data security, adopting NGS poses challenges for labs with limited staff and infrastructure.
To empower small and decentralized labs to easily adopt NGS testing, QIAGEN has launched a new secondary analysis solution for oncology and inherited disease applications that enables high-throughput secondary analysis for use with any clinical NGS data. QCI Secondary Analysis is an agnostic, cloud-based software-as-a-service (SaaS) solution that supports all QIAGEN QIAseq panels and seamlessly integrates with QCI Interpret, QIAGEN’s clinical variant interpretation and reporting software, to deliver highly scalable and customizable Sample to Insight workflows for oncology and inherited disease applications.
“Our goal is to empower molecular testing labs, regardless of size, budget, and experience, to leverage the power of comprehensive genomic information to advance precision medicine in every setting. Due to NGS adoption barriers, including complexity and cost, a vast majority of small- to mid-size molecular laboratories rely on limited single-gene tests or choose to outsource sample testing for more comprehensive NGS analysis. However, with the launch of our new NGS secondary analysis software, we are making NGS testing more accessible to decentralized labs.”
Jonathan Sheldon, Senior Vice President of QIAGEN Digital Insights. “
Tweet
“QCI Secondary Analysis is particularly valuable for labs looking to start running NGS-based tests because it’s a turnkey solution with easy-to-use features for the everyday lab technician. With the availability of this new solution, QIAGEN has simplified the whole bioinformatics pipeline, providing an integrated workflow that minimizes resource investment and maximizes productivity.”
Can Koşukcu, Senior Bioinformatics Application Scientist of DiagnoSeq, an early-access customer of QCI Secondary Analysis.
Tweet
Expanding on the QIAGEN Clinical Insights (QCI) portfolio, QCI Secondary Analysis is designed to streamline analysis from a range of assay types, enabling labs to process more sequencing data without extensive time and resource investment. The turnkey solution is deployed on the QIAGEN Clinical Cloud, a secure cloud environment ensuring the highest degree of isolation and data protection, including compliance with ISO 27001, General Data Protect Regulation (GDPR), and the Health Insurance Portability and Accountability Act (HIPPA) requirements.
While QCI Secondary Analysis is a plug-in-play solution that can support any panel, NGS instrument or software, the true value of this new offering is how it complements QIAGEN’s Sample to Insight portfolio. QCI Secondary Analysis is validated for use for all QIAseq panels, can be used with LightSpeed Clinical, a new software module within QIAGEN CLC Genomics Workbench Premium that enables ultra-fast NGS analysis, and directly integrates with QCI Interpret, QIAGEN’s variant interpretation and reporting platform that has been trusted to analyze and interpret more than 3.5 million NGS patient test cases worldwide.
Learn more about QCI Secondary Analysis here.
Every clinical NGS lab is unique. That’s why QIAGEN offers a comprehensive portfolio of secondary analysis solutions designed to meet the needs of each lab. Take our quiz to find out which secondary analysis solution is right for you based on your lab’s computing resources, personnel expertise, and annual sample volume.
We are pleased to announce that the Winter 2023 Release of QCI Interpret Translational, QIAGEN’s web-based software application for the annotation, classification, and research of somatic and germline variants, is now available.
Expanding on the software’s current capabilities, the QCI Interpret Translational Winter 2023 Release brings new variant classification and assessment tools, greater customization, and even more variant content for prevalent hereditary diseases for faster, more informed variant analysis.
QCI Interpret Translational now offers a new optional Triage Mode inline assessment tool to accelerate variant review workflows. The Triage Mode can be toggled on and off (Figure 1).
For novel unassessed variants, the Assessment, Actionability (somatic workflow only), and the Reportability values match the Computed Classification. Users can then add assessment notes (Figure 2). This new feature is intended to help high volume laboratories quickly assess and triage variants.
QCI Interpret Translational’s literature coverage of genes, involved and associated with disease(s), strongly differentiates QCI Interpret Translational from other NGS variant assessment software by providing a fully certified and manually curated bibliography of approximately 1,000 genes with continuous expansion.
In the QCI Interpret Translational Winter 2023 Release, the bibliography coverage is enhanced and expanded with a focus on genes that are routinely tested and proposed for carrier screening by the latest ACMG practice resource (Genetics in Medicine (2021) 23:1793–1806; https://doi.org/10.1038/s41436-021-01203-z).
Specifically, the bibliography coverage was fully certified and manually curated for Tier 3 genes with continued curation of Tier 4 genes, to provide a comprehensive and complete carrier screening interpretation workflow based on the latest ACMG recommendations summarized below:
In QCI Interpret Translational, a new ClinVar column displays the assessment (P, LP, VUS, LB, B) and number of ClinVar submitters as pulled from the QIAGEN Knowledge Base. A hyperlink takes the user to the respective ClinVar VCV page (phenotype agnostic) (Figure 3).
Pathogenic (P), Likely Pathogenic (LP), VUS, Likely Benign (LB), and Benign (B) interpretations sent to ClinVar are tallied. The hyperlink takes the user to the NCBI variant specific page for additional detail.
For the complete QCI Interpret Translational Winter 2023 Release Notes, please contact your QIAGEN Digital Insights account representative or email our support team at ts-bioinformatics@qiagen.com.
QCI Interpret Translational is a web-based software application for the annotation, classification, and research of variants from next generation sequencing (NGS) data in genomic laboratories. Using augmented molecular intelligence and expertly curated content from the QIAGEN Knowledge Base, QCI Interpret Translational uses evidence-based approaches to automatically compute pathogenicity classifications (Pathogenic to Benign) and actionability classifications (Tier 1 to 4) for each alteration according to the 2015 professional guidelines from the American College of Medical Genetics and Association for Molecular Pathology (ACMG/AMP) [1] and the 2017 guideline from the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists (AMP/ASCO/CAP) [2], respectively.
Pathogenicity and actionability classifications in QCI Interpret Translational are accompanied by clear visibility into the criteria and evidence supporting the classifications. This workflow starts with a variant call format (VCF) file, so it is compatible with the output from any NGS platform. The final analysis is sample-specific and includes candidate causal variants, their deep annotations, interpretations, and references specified throughout the assessment process. The assessment process also has customized automation allowing for even more streamlined variant research workflows.
QCI Interpret Translational helps research labs:
[metaslider id=19676]
Day One kicked-off with numerous informational sessions, including talks on the role of AI in clinical decision-making, the importance of standardization for reimbursement, and the tremendous potential of genomic profiling in disease prevention, diagnosis, and treatment.
Dan Richards, Vice President of Biomedical Informatics at QIAGEN, spoke about the clinician's current challenge of curating all the evidence he or she needs to confidently sign-off on variant reports before they go to the prescribing physician. QIAGEN Clinical Insight (QCI) and N-of-One were featured as solutions providing options for either in-house curation with tailored workflows or on-demand curation services.
On Tuesday morning, the conversation continued with a panel hosted by Sean Scott, Chief Business Officer of Clinical Genomics and Bioinformatics at QIAGEN, that discussed the emergence and application of real-world evidence in the clinical setting, especially in precision diagnostics and clinical trial protocol design.
The panel consisted of Raju K Pillai, MD, Hematopathologist and Molecular Pathologist at City of Hope National Medical Center, James Hadfield, Director and Principal Diagnostic Scientist at AstraZeneca, and Sheryl Krevsky Elkin, Chief Scientific Officer of N-of-One.
Also on Tuesday morning, Mary Napier, Associate Director of NGS Strategy at QIAGEN, gave a timely talk on how diagnostic labs and pharma companies can gain a comprehensive understanding of tumor mutational burden signature by implementing our new QIAseq Tumor Mutational Burden panel.
What does she mean by "comprehensive"?
Find out here!
Thank you to everyone who visited the QIAGEN booth, we truly enjoyed talking to all of you about the industry challenges, and changes you see happening now and in the future.
See you at our next event:
Advances in Genome Biology and Technology (AGBT) 2019 in Marco Island, Florida!
February 27th - March 2nd
Want to know more about our clinical solutions and real-world evidence?
The contest was called to address a current industry challenge: standardizing variant interpretation and reporting. The increasing demand for next-generation sequencing (NGS)-based tests has led to a high degree of variability in how members of the global molecular genetics and pathology community classify variants and prepare final reports. To better understand the limitations of standardization and move forward in the same direction, Agilent Technologies, Thermo Fisher Scientific, and QIAGEN engaged in a friendly competition to determine which company had the most accurate and consistent NGS analysis and interpretation platform: the Alissa Interpret platform, Ion Torrent platform, and QIAGEN's Biomedical Genomics Workbench and QIAGEN Clinical Insight (QCI™) Interpret, respectively.
Erasmus University Medical Center (Erasmus MC) Rotterdam generated sequence data from five clinical samples using Thermo Fisher’s Ion Torrent platform. The three contestants were given this sequence data and instructed to identify clonal and subclonal mutations in the tumors down to an allele frequency level of at least five percent. Then, the contestants were asked to identify and annotate the variants, calculate allele frequency, and interpret the variants according to a five-tier classification system ranging from “benign” to “clinically significant.”
This was no easy task.
Initially, seven companies expressed interest in meeting the challenge. In the end, only three crossed the finish line. According to Professor Winand Dinjens, the organizer of this year’s competition, and head of molecular diagnostics in the Department of Pathology at Erasmus MC Rotterdam, most contenders dropped out after struggling to analyze the sequencing data, which was produced with the Ion S5 XL System, a version of the Ion Torrent platform. As the race unfolded, unfamiliarity with the provided sequencing data caused more than half of the competitors to exit the track.
So, was there a home advantage?
The sequencing data in question was produced by the Ion Torrent platform, which means the Thermo Fisher team analyzed the data using tools custom-built to work with this type of sequence data. For example, during the variant calling process, the Thermo Fisher team was able to apply “flow space” information for each base as it related to Ion Torrent chemistry.
Even so, QIAGEN didn’t back down.
While Thermo Fisher may have had greater familiarity with this particular “track,” QIAGEN’s bioinformatics solutions are open platforms and have experienced over 750,000 “races” on all types of “tracks” across the world. The QIAGEN Knowledge Base is the industry’s largest, most up-to-date clinical database with the direct experience of analyzing over 750,000 human samples. This cumulative experience, in addition to more than 16 million knowledge base findings across 23,000 genes, gives QCI Interpret greater scope and depth.
For each of the five cancer samples, Erasmus supplied FASTQ files plus aligned BAM files, from which the task was to perform variant calling and interpretation and to generate a list of clinically reportable findings. Tim Bonnert, QIAGEN’s Associate Director of Bioinformatics Field Application Scientists, EMEA first used QIAGEN’s Biomedical Genomics Workbench to process the FASTQ files and perform the variant calling. Then he assessed the variants with QCI Interpret, which has curated content that triggered built-in ACMG/AMP and AMP/ASCO/CAP guidelines.
When the results from all contenders were in, none were identical.
QIAGEN’s software solutions performed significantly better than the competition. The organizers stated that there were a total of 12 variants across the five samples. QIAGEN reported 11 of the 12 variants; the variant had been identified in a homopolymer region, and the QIAGEN team identified this variant as a potential false positive. However, this classification does not change the overall clinical actionability recommendation for the patient. By contrast, Agilent and Thermo Fisher missed multiple calls. In some cases, neither platform detected variants in a sample that did in fact have clinically actionable findings; for example, the Torrent Variant Caller pipeline generated no calls for three clinically meaningful variants.
Even though QIAGEN outperformed competitors and achieved almost 100% concordance, these kinds of “battles” illustrate the importance of having pre-defined and clear standards for bioinformatics workflows. Classification and reporting of variants to healthcare providers is critical for patient care. This process requires: accurate reporting of the tumor response to targeted therapy; establishment of professional guidelines for patient care; and collaborative institutional clinical trials, thereby supporting the need for standardization among laboratories performing these tests.
According to Bonnert, “While Erasmus MC no doubt had these standards nailed down in their routine testing pipelines, for this competition there was, for example, uncertainty about required depth of coverage, acceptable distance into the intron, and other confidence metrics and standards that we believe are essential to any routine clinical bioinformatics approach. The need for standards in routine testing also extends to employing clearly defined rules and assessment criteria supported by curated clinical evidence.”
Standards are important for ensuring consistency of secondary and tertiary analysis workflows and for generating actionable data. The faithful detection of variants from Ion Torrent data by the Biomedical Genomics Workbench and the standardized clinical decision support provided by QCI Interpret proved the winning combination.
We are honored to have participated in the Battle of the Bioinformatics Pipelines. Here at QIAGEN, we are committed to building the most reliable, robust and technologically-advanced bioinformatics tools that are sequencer-agnostic because we want to empower more labs, more clinicians, and more patients to do and know more. Just as our pipeline proved victorious with Ion Torrent data in this battle, our research and clinical solutions work successfully with QIAGEN’s own GeneReader platform, as well as with data from Illumina.
Get in touch with one of our experts today! CONTACT US
The February 2016 issue of Medical Lab Observer features a story co-authored by two QIAGEN Bioinformatics executives, Ramon Felciano and Michael Hadjisavas.
The story highlights the disparity between the increasing sophistication of genetic testing and the cumbersome process of variant analysis. It outlines a few key reasons for this growing gap, including the complexity of some variants, the traditional and painstaking process by which labs categorize variants, and the lack of consistency in reporting. The authors make the case that, to keep up with demand for genetic testing, the analysis piece of the puzzle needs to be fully automated, streamlined, and scalable. They call for a community-wide approach to overcome these challenges, such as the Allele Frequency Community. By sharing their resources, communities increase the value of the repository and not only help develop the market, but also improve patient diagnostics and care.
Check out the story: "Soaring demand for genetic testing highlights need for streamlined data interpretation". The article does a great job of addressing many key considerations regarding genetic testing interpretation, the resulting glut of data, and the increasing gap between the two. We hope you enjoy reading!
Read the full story
Read more about our products
