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.
PFZ38G09_PFZ38G09
PFZ38G09_PFZ38G09 is a Labrador Retriever from the Hayward2016 research cohort. One of 14,478 dogs who built the atlas.
See PFZ38G09_PFZ38G09 in the atlasPFZ38G09_PFZ38G09 sits near the center of the Labrador Retriever cluster - genetically very typical for the breed.
- Predicted medium by the six body-size genes the atlas reads (IGF1, HMGA2, SMAD2, LCORL, STC2, ADAMTS17).
- Carries one copy of the FGF4 chondrodysplasia retrogene.
- Carrier of the RSPO2 wire-coat variant (single copy).
The five dogs in the atlas whose genomes sit closest to PFZ38G09_PFZ38G09's. Click any of them to keep exploring.
PFZ38G09_PFZ38G09 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 75%
- Golden Retriever 25%
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 0.626
z 5.791
The 3 PCs on which PFZ38G09_PFZ38G09 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr14:35,252,647 loading 0.0345
- chr7:40,535,333 loading 0.0300
- chr17:50,105,121 loading -0.0291
- chr18:29,956,251 loading 0.0345
- chr26:19,556,698 loading 0.0316
- chr21:15,780,220 loading -0.0288
- chr7:21,167,050 loading 0.0346
- chr25:32,919,094 loading 0.0335
- chr7:21,698,587 loading 0.0335