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.
Flat_Coated_Retriever_7018
Flat_Coated_Retriever_7018 is a Flat Coated Retriever from the Hedan research cohort. One of 14,478 dogs who built the atlas.
See Flat_Coated_Retriever_7018 in the atlasFlat_Coated_Retriever_7018 sits near the center of the Flat Coated Retriever cluster - genetically very typical for the breed.
- Predicted large 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 Flat_Coated_Retriever_7018's. Click any of them to keep exploring.
Flat_Coated_Retriever_7018 sits firmly in the Flat Coated Retriever cluster.
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.
From the CanVAS (Hedan cohort) . Breed-page reference: Flat Coated 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 3.880
z 6.985
The 3 PCs on which Flat_Coated_Retriever_7018 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr1:34,965,612 loading 0.0332
- chr1:34,919,792 loading 0.0296
- chr13:27,716,342 loading 0.0283
- chr29:21,886,817 loading 0.0283
- chr32:36,857,898 loading -0.0278
- chr37:28,513,334 loading -0.0274
- chr3:66,859,090 loading 0.0315
- chr5:34,597,402 loading -0.0299
- chr10:40,957,281 loading -0.0291