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.
3143_3143
3143_3143 is a Labrador Retriever from the Hayward2016 research cohort. One of 14,478 dogs who built the atlas.
See 3143_3143 in the atlas3143_3143 sits near the center of the Labrador Retriever cluster - genetically very typical for the breed.
- Predicted giant by the six body-size genes the atlas reads (IGF1, HMGA2, SMAD2, LCORL, STC2, ADAMTS17).
- Carries both copies of the FGF4 chondrodysplasia retrogene - the short-leg variant in Dachshund, Pembroke Corgi, Basset Hound.
- Carrier of the RSPO2 wire-coat variant (single copy).
The five dogs in the atlas whose genomes sit closest to 3143_3143's. Click any of them to keep exploring.
3143_3143 sits in the Labrador Retriever cluster, with genome overlap to Golden Retriever - sister breeds nearby in the atlas.
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 76%
- Golden Retriever 24%
From the CanVAS (Hayward2016 cohort) . Breed-page reference: Labrador 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 0.720
z 5.350
The 3 PCs on which 3143_3143 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr18:29,956,251 loading 0.0345
- chr26:19,556,698 loading 0.0316
- chr21:15,780,220 loading -0.0288
- chr29:37,511,112 loading 0.0311
- chr15:28,326,342 loading -0.0273
- chr35:8,740,750 loading 0.0271
- chr23:20,231,163 loading 0.0295
- chr22:42,651,822 loading -0.0294
- chr27:39,738,665 loading 0.0291