VarCover

VarCover optimizes selection of minimal sets of reference samples that cover specified target alleles for clinical genetic testing.

Key Features:

• Input formats: Accepts variant identifiers such as rsIDs and Variant Call Format (VCF) files as input.
• Min-set cover solution: Implements an approximate min-set cover algorithm via the SetCoverPy package that incorporates sample weights and preselection strategies to identify a near-minimal set of samples covering specified alleles.
• Sample weighting: Leverages minor allele frequency spectrum-derived sample weights to prioritize samples that increase coverage of target alleles.
• Singleton preselection: Preselects samples possessing singleton target alleles to reduce computational processing time for large target-allele sets (e.g., >100).

Scientific Applications:

• Reference-material selection: Identifies minimal sets of reference samples for clinical genetic testing laboratory validation and reference-material selection.
• Coverage of ACMG-recommended genes: Applied to medically actionable genes recommended by the American College of Medical Genetics and Genomics (ACMG) to ensure coverage of pathogenic or likely pathogenic alleles.
• Dataset application and performance example: In a test case of 237 putatively pathogenic variants across 56 ACMG-recommended genes, VarCover identified 140 reference-material samples from the 1000 Genomes Project.

Methodology:

Accepts variant files and identifies target alleles; uses SetCoverPy to apply sample weights and preselect samples with singleton target alleles to optimize coverage and computational efficiency; evaluates number of samples, covered alleles, and processing time across subsets of target alleles.