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.
GRe_GT217_GRe_GT217
GRe_GT217_GRe_GT217 is a Golden Retriever from the Shannon research cohort. One of 14,478 dogs who built the atlas.
See GRe_GT217_GRe_GT217 in the atlasGRe_GT217_GRe_GT217 sits well inside the Golden Retriever cluster - a fairly typical example.
- 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 GRe_GT217_GRe_GT217's. Click any of them to keep exploring.
GRe_GT217_GRe_GT217 sits in the Golden Retriever cluster, with genome overlap to Labrador 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.
- Golden Retriever 77%
- Labrador Retriever 23%
From the CanVAS (Shannon cohort) . Breed-page reference: 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 11.321
z 7.905
The 3 PCs on which GRe_GT217_GRe_GT217 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr29:25,388,461 loading 0.0320
- chr9:34,293,305 loading 0.0320
- chr6:50,176,215 loading 0.0305
- chr8:13,394,852 loading 0.0320
- chr30:2,998,314 loading 0.0313
- chr12:26,709,882 loading 0.0290
- chr1:73,451,600 loading 0.0356
- chr1:69,785,342 loading 0.0343
- chr18:18,333,364 loading 0.0329