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.
cHD15_80_cHD15_80
cHD15_80_cHD15_80 is labelled Labrador Or Golden Retriever in the Biasoli cohort - a catch-all CanVAS label, not a literal ancestry call. One of 14,478 dogs who built the atlas.
See cHD15_80_cHD15_80 in the atlascHD15_80_cHD15_80 sits at the edge of the Labrador Or Golden Retriever cluster but still well within it.
- Predicted large by the six body-size genes the atlas reads (IGF1, HMGA2, SMAD2, LCORL, STC2, ADAMTS17).
- Carries one copy of the FGF4 chondrodysplasia retrogene.
- Carrier of the RSPO2 wire-coat variant (single copy).
The five dogs in the atlas whose genomes sit closest to cHD15_80_cHD15_80's. Click any of them to keep exploring.
cHD15_80_cHD15_80'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 75%
- Golden Retriever 25%
From the CanVAS (Biasoli cohort) . Breed-page reference: Labrador Or Golden Retriever.
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 0.495
z 6.029
The 3 PCs on which cHD15_80_cHD15_80 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr21:19,144,029 loading 0.0303
- chr13:28,713,034 loading -0.0303
- chr15:5,912,708 loading 0.0300
- chr13:666,991 loading 0.0347
- chr25:4,215,319 loading -0.0336
- chr18:33,604,976 loading 0.0307
- chr18:29,956,251 loading 0.0345
- chr26:19,556,698 loading 0.0316
- chr21:15,780,220 loading -0.0288