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.
FJ10_FJ10
FJ10_FJ10 is labelled Village Dog Fiji Viti Levu in the Shannon cohort - a catch-all CanVAS label, not a literal ancestry call. One of 14,478 dogs who built the atlas.
See FJ10_FJ10 in the atlasFJ10_FJ10 is a strong genetic outlier within the Village Dog Fiji Viti Levu cluster - among the most distinctive examples of their 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.
- Wire-coat furnishings - the eyebrow + beard variant at RSPO2.
The five dogs in the atlas whose genomes sit closest to FJ10_FJ10's. Click any of them to keep exploring.
FJ10_FJ10's genome decomposes mostly into German Shepherd, 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.
- German Shepherd 85%
- Golden Retriever 15%
From the CanVAS (Shannon cohort) . Breed-page reference: Village Dog Fiji Viti Levu.
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 1.857
z 1.276
The 3 PCs on which FJ10_FJ10 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr6:57,387,289 loading 0.0303
- chr14:13,904,420 loading -0.0294
- chr30:3,709,721 loading 0.0293
- chr20:38,047,521 loading 0.0380
- chr20:38,715,188 loading -0.0374
- chr20:38,805,558 loading -0.0370
- chr23:3,426,742 loading 0.0355
- chr23:3,756,166 loading 0.0335
- chr4:38,305,840 loading 0.0333