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.
GRLS_grlsC41FH5JJ
GRLS_grlsC41FH5JJ is a Golden Retriever from the GRLS research cohort. One of 14,478 dogs who built the atlas.
See GRLS_grlsC41FH5JJ in the atlasGRLS_grlsC41FH5JJ is a strong genetic outlier within the Golden Retriever cluster - among the most distinctive examples of their breed.
- 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 GRLS_grlsC41FH5JJ's. Click any of them to keep exploring.
GRLS_grlsC41FH5JJ 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 71%
- Labrador Retriever 29%
From the Golden Retriever Lifetime Study . 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 9.297
z 8.817
The 3 PCs on which GRLS_grlsC41FH5JJ scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr22:1,996,400 loading 0.0426
- chr22:1,969,643 loading -0.0423
- chr22:2,473,315 loading 0.0395
- chr23:13,507,176 loading 0.0356
- chr6:36,116,228 loading 0.0355
- chr23:14,586,660 loading 0.0337
- chr3:72,396,064 loading 0.0333
- chr10:25,699,634 loading 0.0321
- chr13:22,942,852 loading 0.0315