Over the past several years, sequencing technologies have evolved at an unprecedented rate making high-throughput genetic screening more accurate and affordable. This has redefined the scale, scope, precision and power of the study of human pathophysiology. Genetic defects are being discovered and characterized far more often, paving the way to new treatments of previously untreatable diseases.
However, such discoveries mostly happen in specialized laboratories with access to high-performance computing resources and a team of skilled bioinformaticians/computational biologists. At Genavli we believe that in-house computing resources and bioinformatics expertise should not be a hurdle in studying, diagnosing and treating genetic disorders. Our aim is to overcome common problems that make genetic discoveries out of reach for a large proportion of scientists. We make sequence analysis and interpretation easily accessible to all research communities.
The Genavli Research Platform consists of two basic components - Genome Analysis Engine (GAE) and Genome Interpretation Engine (GIE). GAE is a scalable computational resource with simplified ways to implement industry standard or custom sequence analysis workflows. GIE provides a web interface that integrates user data with a wide array of biological and clinical annotations while allowing the user to easily prioritize phenotype-dependent variants. Together, GAE and GIE provide a seamless workflow that transform incomprehensible raw genomic data into biologically relevant answers.
Genome Analysis Engine (GAE)
Powered by Google Genomics, GAE offers the flexibility to analyze your data following the GATK best-practices or implement your own workflow tailored for your project. No prior bioinformatics knowledge or expertise is needed. Upload your raw data, choose a workflow and fire up the analysis. We will take care of the rest while you focus on science.
Genome Interpretation Engine (GIE)
GIE is an extension of our Genome Analysis Engine (GAE) and is designed to use the power of Google’s Big Data tools and a plethora of genome annotation resources to create a powerful interface that will make variant prioritization seem trivial. We have combined decades of our experience with cutting-edge Big Data tools to help advance your research and discover new mechanisms underlying both common and rare diseases.