We’re pleased to introduce the availability of the gnomAD dataset in our latest Ingenuity Variant Analysis release. Within the Common Variants filter there is now a new population to filter common variants. If you’re an existing customer, you can log in here.
With Ingenuity Variant Analysis™, you can find disease-causing variants faster, and with fewer false leads, by tapping into the knowledge of millions of scientific findings. Based on 16+ years of expert manual curation of the scientific literature, our Knowledge Base is the gold standard for genome interpretation. By indexing all known disease-causing biological processes, we can deliver new insights and increased likelihood of homing in on the causal variant you’re seeking.
Imagine solving the toughest genetic cases by having the world’s biological knowledge at your fingertips. Our suite of powerful genetics and statistical analysis tools helps you narrow down variants through an interactive series of filters. The filter cascade lets you focus on the disease-causing variants most likely to be implicated in the phenotype of interest.Full release summary
Scientists all over the world have accelerated their research by analyzing more than 400,000 human samples using Ingenuity Variant Analysis. Our Knowledge Base has contributed to more than 5,500 peer-reviewed genomics publications from leading labs across the globe. Read a case study and learn why Ingenuity Variant Analysis is quickly becoming the industry standard for NGS variant interpretation.Read a case study
It can be expensive and time-consuming to study the number of genomes it takes to understand a disease. Ingenuity Variant Analysis is your gateway to extensive cohorts of high-quality, ethnically and phenotypically diverse human genome samples. They provide a set of healthy controls for rapid discovery and validation of causal elements of disease.
By using the filtering in Ingenuity Variant Analysis, we were able to find the gene which then led to the identification of this syndrome.
Dr. Hywel Williams, Centre for Translational Omics in the University College London’s Institute of Child Health (GOSgene)
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