Tute Genomics, a Salt Lake City, Utah-based bioinformatics company, recently launched its first product for the next-generation sequence data analysis market: a cloud-based interpretation engine for annotating and prioritizing genetic variants to help researchers better diagnose disease and develop more targeted treatments.
The product, which shares the company's name, is based on Annotate Variation, or ANNOVAR, a well known open source program for functionally annotating variants found in species such as human, mouse, worm, fly, and yeast. ANNOVAR was developed by Kai Wang, an assistant professor of psychiatry and preventative medicine at the University of Southern California. Wang is the president of Tute Genomics, which he co-founded in 2012 with CEO Reid Robison. It extends the software by offering additional sources of annotation as well as adding a proprietary method of ranking potentially harmful variants.
Tute — which means person in Na'vi, the fictional language of the inhabitants of the equally fictional moon Pandora in the 2009 film Avatar — officially unveiled the software at the American Society for Human Genetics meeting in Boston last month. The six-person company is currently wrapping up a seed funding round during which it raised over $1 million from a number of investors and is working on two other products that will be launched at later dates.
Meanwhile, it hopes that its flagship product picks up steam in the marketplace finding use both in research and clinical settings. According to the company, Tute Genomics streamlines the variant annotation and interpretation process by offering more user-friendly access to ANNOVAR's capabilities, which are widely used in the scientific community to analyze and filter lists of single nucleotide variants, insertions, and deletions. It also believes that the new features its product adds to the program will help researchers prioritize and analyze variants faster and more cost effectively, Robison told BioInform.
For example, Tute's engine pulls in annotation information from more sources than the open source version of ANNOVAR does, he said. Currently, it includes annotations from more than 60 sources including repositories such as ClinVar and the Human Gene Mutation Database. It also has a proprietary machine learning-based technique that it uses to prioritize candidate genes and variants based on how likely they are to be harmful. Tute has filed a provisional patent for the method, which combines all of the known information about candidate variants — such as PolyPhen and Sift scores and allele frequency — into a single so-called Tute score that’s then used to rank the mutations.
Furthermore, by relying on the cloud for compute power, Tute's engine addresses issues of scalability and storage, Robison said. In that environment, users have room to analyze multiple genomes or exomes at a time, enabling large-scale comparison studies by extension, as well as space to securely store their data. Also the cloud's distributed infrastructure makes it possible to speed up the annotation process, he said — Tute can analyze data from an entire human genome in under 15 minutes instead of the hours required by some current software.
As it goes to market, Tute is hoping that Annovar's reputation in the analysis space will make its product attractive to potential customers in pharmaceutical and biotechnology companies as well as clinical laboratories who have their pick of similar products from firms such as Omicia, Knome, and Ingenuity — the latter now owned by Qiagen.
The company also believes it prices are competitive. It lets first-time users sign up for accounts and analyze four genomes or exomes for free. After that, Tute charges $250 per genome or exome for analysis with that cost also covering six months of data storage on its cloud infrastructure — a lower price point than at least one current offering where customers are charged $500 per genome, Robison noted.
There's also an option for customers to analyze data from gene panels for between $50 and $100 per panel depending on the number of genes. Tute is also willing to negotiate discounted pricing for academic customers looking to analyze bulk samples.
"This sets the barrier quite low for entry as any lab can jump in, try it out for free or buy a few for a small project without having to invest a lot in expensive software, long-term commitments, or appliances," Robison said.
So far Tute says that around 125 users from places such as Affiliated Genetics, a genetic testing lab based in Salt Lake City, Baylor University, Columbia University, and the University of Southern California have signed up for accounts. It also has customers in a number of unnamed pharma and biotech companies and is negotiating agreements with a few more, Robison said.
Separately, Tute is working on two additional products for its portfolio. These include MyGene, a mobile application that will let researchers and clinicians explore recessive mendelian traits and pharmacogenetic variants in patients' genomes and exomes. Tute has launched a pilot program where currently more than 100 early adopters are testing the app on a dataset of 20 genomes and providing feedback to the company. It expects to launch the app later this year. It is also working on a variant calling pipeline but it is not providing details about the product at this time.