VarCards2: an integrated genetic and clinical database for ACMG-AMP variant-interpretation guidelines in the human whole genome

Abstract

VarCards, an online database, combines comprehensive variant- and gene-level annotation data to streamline genetic counselling for coding variants. Recognising the increasing clinical relevance of non-coding variations, there has been an accelerated development of bioinformatics tools dedicated to interpreting non-coding variations, including single-nucleotide variants and copy number variations. Regrettably, most tools remain as either locally installed databases or command-line tools dispersed across diverse online platforms. Such a landscape poses inconveniences and challenges for genetic counsellors seeking to utilise these resources without advanced bioinformatics expertise. Consequently, we developed VarCards2, which incorporates nearly nine billion artificially generated single-nucleotide variants (including those from mitochondrial DNA) and compiles vital annotation information for genetic counselling based on ACMG-AMP variant-interpretation guidelines. These annotations include (I) functional effects; (II) minor allele frequencies; (III) comprehensive function and pathogenicity predictions covering all potential variants, such as non-synonymous substitutions, non-canonical splicing variants, and non-coding variations and (IV) gene-level information. Furthermore, VarCards2 incorporates 368 820 266 documented short insertions and deletions and 2 773 555 documented copy number variations, complemented by their corresponding annotation and prediction tools. In conclusion, VarCards2, by integrating over 150 variant- and gene-level annotation sources, significantly enhances the efficiency of genetic counselling and can be freely accessed at http://www.genemed.tech/varcards2/.

Graphical Abstract

Figure 1.

A general workflow of VarCards2. VarCards2 enables the identification of candidate variants from user-uploaded VCF files or through a quick search. For effective prioritization of these variants and the genes associated with genetic diseases, a comprehensive assessment of genomic, genetic, and clinical data sources is imperative. Accordingly, VarCards2 has integrated a range of variant-level and gene-level implications. Note: BA1, Benign Stand-alone; BS1/BS2/BS3/BS4, Benign Strong; BP1/BP3/BP4/BP7, Benign Supporting; PP1/PP2/PP3, Pathogenic Supporting; PM1/PM2/PM4/PM5/PM6, Pathogenic Moderate; PS1/PS2/PS3/PS4, Pathogenic Strong; PVS1, Pathogenic Very Strong.

Figure 2.

Snapshot of variant-level implications in VarCards2. There are three approaches to access variant-level implications, including ‘Quick search’,‘Advanced search’ and ‘Annotate’. As an example, the results of a quick search for the variant ‘chr1:11845727 T > G (GRCh38)’, including predicted the damaging severity of the variants, allele frequencies in different populations and information in disease related database. VarCards2 offers three methods for accessing variant-level implications: 'Quick search', 'Advanced search' and 'Annotate'. For instance, a quick search for the variant 'chr1:11845727 T > G (GRCh38)' yields results that include the damaging severity of the variant, allele frequencies across various populations, and relevant information from disease-associated databases.

Figure 3.

Snapshot of gene-level implications in VarCards2. For instance, details provided for the NPPA gene include basic information, gene functions, associated phenotypes and diseases, gene expression patterns, variant distributions across populations, and drug–gene interactions.