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.
FSp_GT187_FSp_GT187
FSp_GT187_FSp_GT187 is a Finnish Spitz from the Hayward2016 research cohort. One of 14,478 dogs who built the atlas.
See FSp_GT187_FSp_GT187 in the atlasFSp_GT187_FSp_GT187 sits well inside the Finnish Spitz cluster - a fairly typical example.
- Predicted small by the six body-size genes the atlas reads (IGF1, HMGA2, SMAD2, LCORL, STC2, ADAMTS17).
- Carries one copy of the FGF4 chondrodysplasia retrogene.
- Smooth coat. No wire-furnishings variant at RSPO2.
The five dogs in the atlas whose genomes sit closest to FSp_GT187_FSp_GT187's. Click any of them to keep exploring.
FSp_GT187_FSp_GT187 sits in the Finnish Spitz 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.
- Finnish Spitz 76%
- Golden Retriever 15%
- Labrador Retriever 9%
From the CanVAS (Hayward2016 cohort) . Breed-page reference: Finnish Spitz.
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 14.806
z -2.581
The 3 PCs on which FSp_GT187_FSp_GT187 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr7:42,690,827 loading 0.0435
- chr21:34,428,857 loading -0.0342
- chr34:4,429,712 loading -0.0326
- chr3:6,720,531 loading 0.0359
- chr6:29,063,786 loading -0.0348
- chr3:6,180,668 loading 0.0337
- chr10:6,497,921 loading 0.0390
- chr3:5,565,848 loading -0.0351
- chr3:6,720,531 loading 0.0336