GeneCards Version 3: the human gene integrator

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.

Figure 1.

GeneCards Version 3 home page, including search, sample gene, logos and links to the other suite sites, and category/GIFtS-based random gene generator.

Figure 2.

GeneCards Version 3 search results, including detailed minicard expansions which highlight where in the ‘card’ the hits occur.

Figure 3.

Assorted GeneCards genes, of different color-coded categories, source databases, GC identifiers and GIFtS, with associated statistics and examples.

Figure 4.

Alternative splicing diagram in the Transcripts section. Exons with alternative splice sites in different isoforms are broken into Exonic Units (ExUns). The symbol between ExUns indicates an intron, while ‘·’ indicates the junction of two ExUns.

Figure 5.

Enhanced experimental tissue vectors, now including our GeneNote data integrated with normal and cancer data from the Genomics Institute of the Novartis Research Foundation (GNF).

Figure 6.

Snapshot of the SNPs section, highlighting the variety of annotation fields, availability of popups for more detailed information, sort options.

Figure 7.

GeneDecks pathway annotation unification study, aimed at matching differently-named pathways based on overlaps in associated gene-set space.

Figure 8.

Small sample of GeneALaCart output to a batch query. The data can be examined in Excel or serve as input to application-specific computer analysis programs.

Figure 9.

GeneCards architecture and data flow, including offline data collection/ integration and quality assurance processes, relational database, sophisticated search engine and set-centric GeneALaCart and GeneDecks subsystems.

Figure 10.

Sample of GeneCards Version 3 (revision 3.02) gene-centric relational database entities and their relationships, with associated web-card sections.

Figure 11.

The V2 and V3 database collection/integration pipeline and search application flow.

Figure 12.

GeneQArds statistical comparison of GeneCards V2 and V3 search results, for each of the 500 most frequently searched terms in 2008, showing vast improvements for V3. The cases where V2 finds more hits reflect many V2 false positives, some V2 fields that haven’t as yet been incorporated into the V3 database, and some isolated anomalies that are still under investigation.

Figure 13.

(A) Comparison of the number of hits (genes) found by GeneCards and Entrez Gene for two popular searches (EGFR and Retinoblastoma) and (B) the distribution of those hits within the various sections in GeneCards.