LifeMap Releases NGS Phenotyper
By Bio-IT World Staff
January 20, 2015 | LifeMap Sciences has released VarElect, an application that David Warshawsky, CEO of the company, calls a next-generation sequencing phenotyper. The tool leverages LifeMap’s integrated biomedical knowledgebase and discovery platform for biomedical research, which includes GeneCards human gene database; MalaCards human disease database; and LifeMap Discovery, the database of embryonic development, stem cell research, and regenerative medicine.
VarElect and GeneAnalytics are cloud-based tools that are part of the GeneCards Plus suite. VarElect uses data in the various LifeMap databases to prioritize variants entered by the user according to their likely association with a disease or phenotype of interest. Along with GeneCards and MalaCards, VarElect was developed at the Weizmann Institute of Science in Israel. GeneAnalytics, a gene set analysis tool, and LifeMap Discovery were developed within LifeMap Sciences.
“Say you have 600 genes that are the result of an experiment,” Warshawsky says, “and you want to rank and prioritize those 600 genes as they relate to a disease of interest. Within seconds, [VarElect] will create that list for you and also show you all the evidence within the product of how it actually matched each and every one of those 600 genes to the phenotype of interest.”
Dvir Dahary, CEO of Toldot Genetics in Israel, said LifeMap's VarElect has proven to be highly effective in characterizing lists of genes and associating them with specific phenotypes. He and Warshawsky worked together at Compugen about fifteen years ago, and Toldot has been using GeneCards for “many years,” Dahary said.
One of Toldot’s services is to identify the causal mutation in sporadic cases of rare genetic disorders, Dahary explained. His team uses exome sequencing, filters out irrelevant variants, and then prioritizes hundreds of candidate variants using the VarElect tool.
In another use case, Dahary said the company identifies the genetic background of clinical traits by sequencing the genomes of dozens of patients, some that respond and some non-responders for a certain treatment, and associating genetic variations to the drug response.
“This kind of analysis, much like differential expression analyses, results in a list of candidate genes,” he explained. “LifeMap's GeneAnalytics comes to hand at this stage enabling the characterization of the genes in several aspects, e.g. tissue expression, functional enrichment, disease associations and others. The output can markedly increase the confidence in the statistical results by showing relevant associations for the top scoring genes.”
VarElect prioritizes variants by scanning GeneCards and MalaCards looking for direct or indirect relationships between a gene and a disease of interest.
“In the case of a direct link, it will essentially utilize all of the data we have to find an association between gene X and a disease, via a publication, the disease section within GeneCards, it could be via pathways, and so on,” Warshawsky said. “In the case of indirect relationship, Gene X may not be directly to a disease, but it may be related to Gene Y which is related to the disease. The way it will connect Gene X to Gene Y would be protein-protein interactions, pathways, publications, and so on.”
GeneCards and MalaCards rely on more than 100 data sources, everything from the big variant databases like ClinVar and OMIM to propriatry data sources. Those many sources are assembled and organized into a, “well-integrated knowledgebase,” Warshawsky said.
The knowledgebase is accessible to users. Once VarElect returns its findings, researchers are able to dig into data sources, Warshawsky said. It’s very important, he said, that researchers be able to evaluate the sources of the information. “The algorithms we’ve developed in VarElect can do the prioritization, but the user will then be able to see how we actually created the list and the rankings. They can judge for themselves what they want to… use or not use.”
Identifying variants and associating them with phenotypes is only going to become more valuable, Warshawksy believes. “The field is clearly moving in that direction. I don’t think there’s any question that it’s going to become a major part of medicine.”