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.
TIBT_TIBT_35G02
TIBT_TIBT_35G02 is a Tibetan Mastiff from the Spatola research cohort. One of 14,478 dogs who built the atlas.
See TIBT_TIBT_35G02 in the atlasTIBT_TIBT_35G02 is a strong genetic outlier within the Tibetan Mastiff 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).
- 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 TIBT_TIBT_35G02's. Click any of them to keep exploring.
TIBT_TIBT_35G02 sits in the Tibetan Mastiff cluster, with genome overlap to Labrador Retriever, and 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.
- Tibetan Mastiff 51%
- Labrador Retriever 28%
- Golden Retriever 21%
From the CanVAS (Spatola cohort) . Breed-page reference: Tibetan Mastiff.
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 5.742
z 4.953
The 3 PCs on which TIBT_TIBT_35G02 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr21:30,613,458 loading 0.0378
- chr28:5,497,677 loading 0.0367
- chr28:5,428,661 loading 0.0358
- chr16:48,608,303 loading 0.0348
- chr13:24,655,299 loading -0.0330
- chr23:1,734,032 loading 0.0330
- chr26:5,045,393 loading 0.0400
- chr26:4,196,092 loading -0.0355
- chr26:4,873,718 loading -0.0344