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.
PFZ16H02_PFZ16H02
PFZ16H02_PFZ16H02 is a Great Pyrenees from the Hayward2016 research cohort. One of 14,478 dogs who built the atlas.
See PFZ16H02_PFZ16H02 in the atlasPFZ16H02_PFZ16H02 sits well inside the Great Pyrenees cluster - a fairly typical example.
- Predicted giant by the six body-size genes the atlas reads (IGF1, HMGA2, SMAD2, LCORL, STC2, ADAMTS17).
- Standard leg length. No chondrodysplasia retrogene variant.
- Carrier of the RSPO2 wire-coat variant (single copy).
The five dogs in the atlas whose genomes sit closest to PFZ16H02_PFZ16H02's. Click any of them to keep exploring.
PFZ16H02_PFZ16H02 sits in the Great Pyrenees cluster, with genome overlap to Golden Retriever, and 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.
- Great Pyrenees 84%
- Golden Retriever 9%
- Labrador Retriever 7%
From the CanVAS (Hayward2016 cohort) . Breed-page reference: Great Pyrenees.
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 -2.522
z 5.098
The 3 PCs on which PFZ16H02_PFZ16H02 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr22:27,265,197 loading 0.0431
- chr5:72,529,391 loading 0.0328
- chr10:5,349,288 loading 0.0317
- chr1:70,040,058 loading 0.0369
- chr1:99,414,793 loading -0.0351
- chr24:7,157,643 loading 0.0343
- chr25:1,742,133 loading 0.0401
- chr28:2,607,542 loading 0.0393
- chr25:1,819,027 loading 0.0392