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.
Chern_City_Chern_City_52
Chern_City_Chern_City_52 is a Feral Dog Chernobyl from the Spatola research cohort. One of 14,478 dogs who built the atlas.
See Chern_City_Chern_City_52 in the atlasChern_City_Chern_City_52 is a notable Feral Dog Chernobyl - distinctive within 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 Chern_City_Chern_City_52's. Click any of them to keep exploring.
Chern_City_Chern_City_52 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 57%
- Golden Retriever 43%
From the CanVAS (Spatola cohort) . Breed-page reference: Feral Dog Chernobyl.
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 4.236
z 6.027
The 3 PCs on which Chern_City_Chern_City_52 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr4:80,039,364 loading 0.0307
- chr8:13,133,148 loading -0.0301
- chr31:11,367,367 loading 0.0289
- chr1:69,449,779 loading 0.0431
- chr1:69,785,342 loading 0.0329
- chr10:4,740,874 loading 0.0326
- chr24:4,330,562 loading 0.0395
- chr1:76,396,561 loading -0.0378
- chr24:4,851,124 loading -0.0357