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.
GSMD_GSMD_28924
GSMD_GSMD_28924 is a Greater Swiss Mountain Dog from the Spatola research cohort. One of 14,478 dogs who built the atlas.
See GSMD_GSMD_28924 in the atlasGSMD_GSMD_28924 is a strong genetic outlier within the Greater Swiss Mountain Dog cluster - among the most distinctive examples of their breed.
- Predicted giant by the six body-size genes the atlas reads (IGF1, HMGA2, SMAD2, LCORL, STC2, ADAMTS17).
- Standard leg length. No chondrodysplasia retrogene variant.
The five dogs in the atlas whose genomes sit closest to GSMD_GSMD_28924's. Click any of them to keep exploring.
GSMD_GSMD_28924 sits in the Bernese Mountain Dog 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.
- Bernese Mountain Dog 54%
- Labrador Retriever 27%
- Golden Retriever 19%
From the CanVAS (Spatola cohort) . Breed-page reference: Greater Swiss Mountain Dog.
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 -3.765
z 0.629
The 3 PCs on which GSMD_GSMD_28924 scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.
- chr7:44,608,561 loading 0.0331
- chr11:69,439,722 loading 0.0324
- chr1:66,792,676 loading 0.0313
- chr22:4,235,154 loading 0.0445
- chr22:1,892,165 loading 0.0429
- chr22:1,969,643 loading 0.0425
- chr5:75,426,581 loading 0.0352
- chr23:35,872,989 loading -0.0350
- chr16:38,943,549 loading -0.0346