GeneCards Version 3: the human gene integrator

M Safran,T Iny Stein,T Doniger,D Lancet,N Rosen,T Olender,J Alexander,G Stelzer,I Dalah,Y Golan,A Harel,I Bahir,N Nativ,A Sirota-Madi,H Krug,M Shmoish

doi:10.1093/database/baq020

Abstract

GeneCards (www.genecards.org) is a comprehensive, authoritative compendium of annotative information about human genes, widely used for nearly 15 years. Its gene-centric content is automatically mined and integrated from over 80 digital sources, resulting in a web-based deep-linked card for each of >73 000 human gene entries, encompassing the following categories: protein coding, pseudogene, RNA gene, genetic locus, cluster and uncategorized. We now introduce GeneCards Version 3, featuring a speedy and sophisticated search engine and a revamped, technologically enabling infrastructure, catering to the expanding needs of biomedical researchers. A key focus is on gene-set analyses, which leverage GeneCards’ unique wealth of combinatorial annotations. These include the GeneALaCart batch query facility, which tabulates user-selected annotations for multiple genes and GeneDecks, which identifies similar genes with shared annotations, and finds set-shared annotations by descriptor enrichment analysis. Such set-centric features address a host of applications, including microarray data analysis, cross-database annotation mapping and gene-disorder associations for drug targeting. We highlight the new Version 3 database architecture, its multi-faceted search engine, and its semi-automated quality assurance system. Data enhancements include an expanded visualization of gene expression patterns in normal and cancer tissues, an integrated alternative splicing pattern display, and augmented multi-source SNPs and pathways sections. GeneCards now provides direct links to gene-related research reagents such as antibodies, recombinant proteins, DNA clones and inhibitory RNAs and features gene-related drugs and compounds lists. We also portray the GeneCards Inferred Functionality Score annotation landscape tool for scoring a gene’s functional information status. Finally, we delineate examples of applications and collaborations that have benefited from the GeneCards suite.Database URL: www.genecards.org

Highlights

With the recent accumulation of data from worldwide genome projects, the individual scientist faces the time consuming and laborious task of sifting through the expanding labyrinth of gene information
We envision that its updated functionality and new infrastructure will continue to provide an effective research and development platform for many years to come, and look forward to pursuing more adventures
The authors thank the reviewers for crucial insights and suggestions that have helped improve this manuscript, Elena Matusevich and Yakov Perlman for their initial implementation of GeneCards Version 3, David Warshawsky for providing the model and data sources for highly-targeted reagents, Edna Ben-Asher and Orit Shmueli for defining the initial SNP filtering algorithms, Ido Zak for improving its implementation, Ohad Greenspan for implementing the alternative splicing diagram, and Liora Strichman-Almashanu for her mouse phenotype initiative, for pioneering GeneQArds, and for initial V3 data modeling work

Summary

Introduction

With the recent accumulation of data from worldwide genome projects, the individual scientist faces the time consuming and laborious task of sifting through the expanding labyrinth of gene information. We found that some of the pathways (named identically or differently) had considerable overlap in their gene-set composition, but none were complete, that some of the pathways were closely related, and that a few inter and intra-source subsets could be identified Annotation unification of this sort, based on the similarity in GeneCards gene-content space detection algorithms, could be expanded to include other [e.g. our Millipore [24] and Sigma-Aldrich [25]] pathways, and perhaps be generalized to include other attributes such as chemical compounds, phenotypes and/or orthologies. The ‘Applications, advantages and future directions’ section below details a variety of examples of research facilitated by GeneALaCart

Methods

Summary