Information Technology Program
Individualized medicine relies heavily on information technology (IT) resources, from early stages of discovery to final applications in patient care.
In the laboratory, next-generation DNA sequencing requires large amounts of computational resources. These include high-speed servers for identifying genomic variants, cloud services and storing petabytes — that is, millions of gigabytes — of data. As Mayo Clinic physicians and scientists discover promising findings and develop new tools, they need IT applications to validate and optimize new laboratory tests and manage clinical trials.
In the clinic, Mayo healthcare teams use the electronic health record to order new genomic-based tests, retrieve test results, and access new and improved decision-support tools that guide clinicians and patients toward individually appropriate therapies.
The Center for Individualized Medicine's Information Technology Program develops these important innovations and makes sure they run seamlessly in research and clinical practice.
Areas of focus
The Omics Data Platform centralizes and manages enormous amounts of omic data that are generated through patient care and research. These data include multiplexed panels, whole-exome sequencing, whole-genome testing results and more. This single infrastructure supports individualized medicine activities in both research and clinical practice, complete with privacy and security controls. Its cloud-based environment allows users to develop research studies, tests, diagnoses and treatments tailored to patients' individual needs.
The IT Program develops workflows, called "pipelines," to sift through massive amounts of scientific data and provide detailed analyses efficiently and accurately. These pipelines support both research teams and patient care specialists such as genetic counselors, genomic nurses and doctors providing personalized care throughout the clinic.
The IT engineering team specializing in genomic technology workbenches and visualization includes software engineers, bioinformaticians and data scientists. Team members collaborate to design, develop and deploy cutting-edge tools tailored for genomic analysis.
The visualization team develops solutions, platforms and tools for various stages of genomic analysis, including sequence alignment, variant calling, annotation and interpretation. The team draws on a deep understanding of genomics to ensure that the tools have the accuracy, speed and scalability to handle large-scale genomic datasets.
In addition to ensuring core functionality, the visualization team places a strong emphasis on user experience and interface design. The team develops intuitive applications that enable researchers and clinicians to interact with genomic data seamlessly.
The IT program supports Mayo Clinic's Medical Genome Facility and associated bioinformaticians by providing computational and storage infrastructure for primary and secondary analysis of next-generation DNA sequencing. Teams working in this area apply software engineering and optimization methods to scientific workflows to make new bioinformatics methods more robust and easier to scale.
The IT Program also verifies and validates bioinformatics workflows as they are translated into clinical laboratories. These bioinformatics methods support researchers as they discover new biomarkers and use them to diagnose and treat patients.
Mayo Clinic's Bioinformatics Core processes many samples from different next-generation sequencing experiments. Multiple analysts work on the primary and secondary processing of the samples, which belong to various investigators and are associated with a wide variety of projects. It is a challenge to track all the related processing data, such as the sample and project metadata, quality-control information, and location of analysis results.
To address this challenge, the IT Program created the next-generation sequencing portal. This portal is the centralized location for accessing next-generation sequencing data, metadata and associated tools. It is an operational "base camp" where different groups can ask questions about sequencing data and get answers quickly — without needing to email the Bioinformatics Core.
The portal also has dashboard views of both primary and secondary analysis processes. These dashboards make it possible to track the progress of ongoing runs and projects as well as the history of previous runs.
The Biological Annotation Data Repository (BioR) system consolidates and centralizes the access and query of biological annotation data. It simplifies the process of downloading, formatting and querying diverse sets of annotations at local or remote data repositories.
The system then facilitates comprehensive annotation of many molecular datasets produced by high-throughput platforms such as next-generation sequencing, proteomics and metabolomics. It allows users to navigate complex biological feature trees and resolve indirect relationships that may exist among annotation sources.
BioR also serves as a source for internally developed annotations that may be generated from experiments done locally or from manual annotation of disease-causing single nucleotide polymorphisms.
Applications
The Clinical Omics Results Exchange connects clinical applications such as Epic and Genomix with researchers and the Mayo Clinic Department of Laboratory Medicine and Pathology. The exchange defines, standardizes and normalizes genomics inputs from multiple data sources and provides this standardized data to patients' electronic health records.
Since 2013, the IT Program has been annotating genomic sequencing results to help interpret and report gene changes found in the results. As the number of gene-phenotype and variant-phenotype associations grows, and annotation sources evolve, scientists need to go back and identify significant changes in genomic sequencing variant results that have been analyzed before. Due to the high volume of results and annotations, automation makes the process of reanalyzing patient data much more efficient and cost-effective.
To meet this need, the IT Program developed the Semi-Automated Reanalysis of Negative Whole Exome/Genome Cases application — RENEW for short. RENEW is an automated re-annotation system. In coordination with upstream systems, it allows users to characterize annotation changes, and supplement existing genomic results with these changes. Then, it filters the results for clinically significant changes that call for manual reinterpretation by genetics experts.
The IT Program developed the Investigator Portal, a sophisticated online platform for Mayo Clinic omics and personalized medicine researchers. The portal provides an integrated environment for managing, analyzing and interpreting complex datasets.
The Investigator Portal is a pivotal tool in omics and personalized medicine research. Its advanced data handling capabilities, collaborative features and user-friendly interface empower researchers to advance individualized medicine research.
The Semi-Automated Variant Interpretation for Principal Investigators (SAVI)-PI application is a technology workbench and analysis pipeline for Mayo Clinic researchers. The analysis pipeline automatically interprets genetic variants by feeding annotation from sources such as ClinVar, HGMD, and CAVA into a rule-based algorithm. It classifies each variant as pathogenic, likely pathogenic, benign, likely benign or of unknown significance. When variants are flagged as pathogenic or likely pathogenic, SAVI-PI manually curates them in the workbench for an expert to review the supporting criteria and make a final classification.
SAVI-PI is web-based and integrated with Investigator Portal. It has an automated variant annotation and prioritization pipeline based in Google Dataflow.
Genomix is a web application in use only at Mayo Clinic. It displays integrated, actionable pharmacogenomics and genomic data in patients' electronic health records and allows healthcare teams to easily interact with these data.
Pharmacogenomics information is currently available to healthcare teams through Epic Hyperspace "Genomic Indicators" activity. The Epic system provides an alert when someone orders a new prescription for a patient with a known drug-gene interaction. But this information is not presented in a way that's easy for users to act on — for example, if a doctor is looking for the best alternative to the drug that was flagged. The Genomix application offers this kind of useable information.