TS-003682 — The CAVALRI (Clinical Assessment of Variant Likelihood Ratios) algorithm is a new development in clinical genomics and diagnostics. Addressing the challenge of identifying diagnostic germline variants in rare genetic diseases, the IP utilizes a likelihood ratio framework to assess genetic mutations’ severity, phenotypic overlap with known diseases, and parental genotype concordance. It provides a scalable solution for rapid and accurate variant interpretation, aiding clinicians and variant scientists in identifying disease-causing variants from vast genomic data. By automating variant prioritization, CAVALRI reduces manual effort and time required for variant analysis, which enables faster diagnoses and potentially reducing diagnostic errors. CAVALRI surpasses existing methods by prioritizing diagnostic germline variants with higher accuracy, even in the presence of noisy computational phenotype sets. innovation in rare disease diagnostic algorithms. With its potential to revolutionize variant interpretation, CAVALRI garners interest from companies specializing in genomic diagnostics, clinical decision support software, and healthcare informatics. Its future development aims to integrate seamlessly into diagnostic laboratories and healthcare systems, streamlining genomic diagnostics and improving patient outcomes.

TS-003669 — SNPDogg is a machine-learning classifier designed to predict the harmfulness of genomic mutations in humans. This tool addresses the challenge of assessing the potential damaging effects of the roughly 3 million mutations present in the human genome, many of which remain uncharacterized. SNPDogg provides users with transparent insights into its prediction process through interpretable graphical displays of feature contributions. Additionally, SNPDogg boasts accuracy comparable to other state-of-the-art tools while offering unique transparency features. It is positioned as a valuable resource for clinicians and researchers involved in variant assessment, offering a user-friendly interface and interpretability that simplifies the evaluation process. Further development of SNPDogg includes plans to expand its capabilities to include scoring for INDELs (insertions/deletions) and native compatibility with the GRCh38 genome build, enhancing its utility and coverage of genetic variants.

TS-000141 — Next Generation Sequencing (NGS) is a sequencing technology characterized by the large volume of generated DNA/RNA sequencing data. However, the cost to analyze NGS data is outstripping the cost to actually produce the data. To circumvent this challenge, the Institute for Genomics Medicine have developed a fully automated and comprehensive analysis tool called CHURCHILL. CHURCHILL’s patented novel parallelization strategy analyzes raw NGS data in a record time.