Bovine and Human Breed-Specific Genome Graphs for Variant Discovery

ETH Zurich researcher Danang Crysnanto provides data supporting experiments with breed-specific augmented reference graphs for cattle and human genomes. The dataset includes simulated reads, variant files, consensus genomes, and whole-genome graphs for Brown Swiss cattle, alongside similar data for human populations. It is organized into compressed folders for cattle and human genome graph experiments.

Use Cases

• Benchmark read mapping accuracy based on simulated short reads from four animals per breed.
• Prioritize genetic variants based on allele frequency filters applied to the provided VCF files.
• Construct whole-genome graphs for specific breeds using variants from multiple chromosomes.
• Evaluate consensus genome generation using liftovered read coordinates and major allele variants.

Strengths

• Includes data for both cattle (Brown Swiss) and human genome experiments, enabling cross-species method comparison.
• Provides specific software tools (vg, liftover, vcf2diploid) used in the accompanying paper.
• Organizes data into distinct parts corresponding to specific analysis sections described in the paper.

Limitations

• Row count and dataset scale are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Danang Crysnanto, ETH Zurich

Collection Method

Data generated for genome graph experiments, likely involving simulation and public reference genomes.