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.
C_TMf_C_TMf4
C_TMf_C_TMf4 is a Tibetan Mastiff from the Chen research cohort. One of 14,478 dogs who built the atlas.
See C_TMf_C_TMf4 in the atlasC_TMf_C_TMf4 sits well inside the Tibetan Mastiff cluster - a fairly typical example.
- Predicted large by the six body-size genes the atlas reads (IGF1, HMGA2, SMAD2, LCORL, STC2, ADAMTS17).
- Carries both copies of the FGF4 chondrodysplasia retrogene - the short-leg variant in Dachshund, Pembroke Corgi, Basset Hound.
- Carrier of the RSPO2 wire-coat variant (single copy).
The five dogs in the atlas whose genomes sit closest to C_TMf_C_TMf4's. Click any of them to keep exploring.
C_TMf_C_TMf4 sits in the Tibetan Mastiff 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.
- Tibetan Mastiff 81%
- Golden Retriever 11%
- Labrador Retriever 9%
From the CanVAS (Chen 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 4.784
z 0.785
The 3 PCs on which C_TMf_C_TMf4 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr6:60,987,558 loading 0.0302
- chr18:25,790,852 loading 0.0293
- chr14:14,074,192 loading -0.0293
- chr13:666,991 loading 0.0347
- chr25:4,215,319 loading -0.0336
- chr18:33,604,976 loading 0.0307
- chr19:4,037,398 loading 0.0415
- chr19:5,321,387 loading 0.0400
- chr19:5,388,895 loading -0.0395