Genome analysis and knowledge-driven variant interpretation with TGex

Dvir Dahary; Yaron Golan; Yaron Mazor; Ofer Zelig; Ruth Barshir; Michal Twik; Tsippi Iny Stein; Guy Rosner; Revital Kariv; Fei Chen; Qiang Zhang; Yiping Shen; Marilyn Safran; Doron Lancet; Simon Fishilevich

doi:10.1186/s12920-019-0647-8

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Genome analysis and knowledge-driven variant interpretation with TGex

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Genome analysis and knowledge-driven variant interpretation with TGex

Dvir Dahary, Yaron Golan, Yaron Mazor, Ofer Zelig, Ruth Barshir, Michal Twik, Tsippi Iny Stein, Guy Rosner, Revital Kariv, Fei Chen, …

BMC Medical Genomics, Vol.12(1), 200

30/Dec/2019

DOI: https://doi.org/10.1186/s12920-019-0647-8

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Abstract

Background: The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient's phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants.

Results: We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform, with remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex's main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex's broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards' recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters. Examining use-cases from a variety of TGex users world-wide, we demonstrate its high diagnostic yields (42% for single exome and 50% for trios in 1500 rare genetic disease cases) and critical actionable genetic findings. The platform's support for integration with EHR and LIMS through dedicated APIs facilitates automated retrieval of patient data for TGex's customizable reporting engine, establishing a rapid and cost-effective workflow for an entire range of clinical genetic testing, including rare disorders, cancer predisposition, tumor biopsies and health screening.

Conclusions: TGex is an innovative tool for the annotation, analysis and prioritization of coding and non-coding genomic variants. It provides access to an extensive knowledgebase of genomic annotations, with intuitive and flexible configuration options, allows quick adaptation, and addresses various workflow requirements. It thus simplifies and accelerates variant interpretation in clinical genetics workflows, with remarkable diagnostic yield, as exemplified in the described use cases.

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Title: Genome analysis and knowledge-driven variant interpretation with TGex
Creators: Dvir Dahary (null) - LifeMap Sciences, Inc.
Yaron Golan (null) - LifeMap Sciences, Inc.
Yaron Mazor (null) - LifeMap Sciences, Inc.
Ofer Zelig (null) - LifeMap Sciences, Inc.
Ruth Barshir (null) - The Weizmann Institute of Science
Michal Twik (null) - The Weizmann Institute of Science
Tsippi Iny Stein (null) - 972WIS_INST___111
Guy Rosner (null) - Tel Aviv Sourasky Medical Center
Revital Kariv (null) - Tel Aviv Sourasky Medical Center
Fei Chen (null) - Childrens Hosp Guangxi Zhuang Autonomous Reg
Qiang Zhang (null) - Childrens Hosp Guangxi Zhuang Autonomous Reg
Yiping Shen (null) - Childrens Hosp Guangxi Zhuang Autonomous Reg
Marilyn Safran (null) - The Weizmann Institute of Science
Doron Lancet (null) - 972WIS_INST___111
Simon Fishilevich (null) - The Weizmann Institute of Science
Resource Type: Journal article
Publication Details: BMC Medical Genomics, Vol.12(1), 200; 30/Dec/2019
Number of pages: 17
Language: English
DOI: https://doi.org/10.1186/s12920-019-0647-8
Grant note: Support for the GeneCards Suite was provided by a Research and Licensing grant from LMS. Additional funding was provided from the WIS Crown Human Genome Center, and an EU grant from PIONEER, a European Network of Excellence for Big Data in Prostate Cancer. Guangxi’s project is supported by the National Key Research and Development Program (2018YFC1002501) and Major Research Plan of the Provincial Science and Technology Foundation of Guangxi (AB16380214). The funding body LMS participated in the design of the study and in the collection, analysis, and interpretation of data, as well as in writing the manuscript, while all other funding bodies had no such roles. There are four authors from LMS, YG, YM, DD and OZ, all of whom had an active role in the project. YG and DD conceived and designed the TGex software; YG and YM developed the TGex code; YG, DD, YM and OZ collaborated with Weizmann institute authors in the integration of the Weizmann’s GeneCards Suite knowledgebase and interpretation algorithms into TGex; DD collaborated with other authors in the analysis and interpretation of the use-cases data; DD and YG collaborated with SF from Weizmann in writing and revising the manuscript. Contributions - TGex was conceived and implemented by LMS and incorporates the WIS GeneCards Suite knowledgebase and gene prioritization/interpretation algorithms. The manuscript was jointly written by the LMS and WIS teams. YG and DD designed and supervised the development of TGex; YG and YM developed the software; GR, RK and DD performed the analyses and interpreted the data of the CRC use-case; YG, YM, DD, MT, RB, OZ, MS, DL and SF designed the integration of the GeneCards Suite knowledgebase and interpretation algorithms within TGex; TIS provided scientific guidance and quality assurance for the software; FC, QZ and YS supervise the clinical genetics workflow at Guangxi; DD and SF wrote the manuscript; YG, RB, GR, RK, MS and DL revised the manuscript; All authors read and approved the final manuscript.
Record Identifier: 993265903303596

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