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.
cHD10_544_cHD10_544
cHD10_544_cHD10_544 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 cHD10_544_cHD10_544 in the atlascHD10_544_cHD10_544 is a notable Labrador Or Golden Retriever - distinctive within the breed.
- Predicted small by the six body-size genes the atlas reads (IGF1, HMGA2, SMAD2, LCORL, STC2, ADAMTS17).
- Carries one copy of the FGF4 chondrodysplasia retrogene.
- Smooth coat. No wire-furnishings variant at RSPO2.
The five dogs in the atlas whose genomes sit closest to cHD10_544_cHD10_544's. Click any of them to keep exploring.
cHD10_544_cHD10_544'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 78%
- Golden Retriever 22%
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 0.257
z 8.809
The 3 PCs on which cHD10_544_cHD10_544 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr11:59,916,847 loading 0.0380
- chr1:13,688,590 loading -0.0336
- chr9:44,269,754 loading 0.0311
- chr8:33,499,010 loading 0.0341
- chr6:30,409,356 loading -0.0338
- chr34:15,382,542 loading -0.0330
- chr29:37,511,112 loading 0.0311
- chr15:28,326,342 loading -0.0273
- chr35:8,740,750 loading 0.0271