AI portrait
This portrait was algorithmically built from this dog's genome: their genotype at 8 morphology loci (coat length, curl, color, ear set, body size, head shape, skull, furnishings) plus their position within the 14,478-dog atlas. The same dog always reproduces the same portrait. A different dog with different alleles gets a different portrait.
SA_1_SA_17AS
SA_1_SA_17AS is labelled Village Dog South Africa 1 in the Spatola cohort - a catch-all CanVAS label, not a literal ancestry call. One of 14,478 dogs who built the atlas.
See SA_1_SA_17AS in the atlasSA_1_SA_17AS sits near the center of the Village Dog South Africa 1 cluster - genetically very typical for the breed.
- Predicted large by the six body-size genes the atlas reads (IGF1, HMGA2, SMAD2, LCORL, STC2, ADAMTS17).
- Standard leg length. No chondrodysplasia retrogene variant.
- Smooth coat. No wire-furnishings variant at RSPO2.
The five dogs in the atlas whose genomes sit closest to SA_1_SA_17AS's. Click any of them to keep exploring.
SA_1_SA_17AS's genome decomposes mostly into Labrador Retriever, with additional weight on Golden Retriever.
Breed similarity from non-negative least squares against 91 breed centroids in PCA-256 space, corrected for atlas sample-size imbalance. Without correction, Goldens (22% of the atlas) leak into every dog's raw NNLS breakdown; with it, the bias falls out. Raw fractions stay in the dataset for re-derivation. Methodology.
- Labrador Retriever 55%
- Golden Retriever 45%
From the CanVAS (Spatola cohort) . Breed-page reference: Village Dog South Africa 1.
Full genotype detail click to expand
The actual allele call at each locus's representative SNP for this dog. Each gene name links to its page where you can see the per-breed frequency table and the direction of effect.
Technical details click to expand
The numbers behind the placement. Useful for researchers reproducing the math or debugging an unexpected position; not interesting to most readers.
y 6.566
z 6.472
The 3 PCs on which SA_1_SA_17AS scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr22:1,996,400 loading 0.0303
- chr22:2,231,766 loading 0.0280
- chr22:3,165,486 loading 0.0275
- chr21:8,227,069 loading 0.0376
- chr16:47,900,123 loading 0.0333
- chr1:24,270,460 loading 0.0312
- chr1:73,451,600 loading 0.0356
- chr1:69,785,342 loading 0.0343
- chr18:18,333,364 loading 0.0329