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CanVAS Spatola · Founder
Cosmic medallion portrait of CHINA_CHINA_4CH, a Village Dog China
AI portrait
About this 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.

CHINA_CHINA_4CH

CHINA_CHINA_4CH is labelled Village Dog China in the Spatola cohort - a catch-all CanVAS label, not a literal ancestry call. One of 14,478 dogs who built the atlas.

See CHINA_CHINA_4CH in the atlas
About CHINA_CHINA_4CH

CHINA_CHINA_4CH sits well inside the Village Dog China cluster - a fairly typical example.

  • Predicted giant by the six body-size genes the atlas reads (IGF1, HMGA2, SMAD2, LCORL, STC2, ADAMTS17).
  • Carries one copy of the FGF4 chondrodysplasia retrogene.
  • Wire-coat furnishings - the eyebrow + beard variant at RSPO2.
CHINA_CHINA_4CH's nearest neighbors

The five dogs in the atlas whose genomes sit closest to CHINA_CHINA_4CH's. Click any of them to keep exploring.

  1. CHINA_CHINA_3CH Village Dog China 16.36
  2. CHINA_CHINA_2CH Village Dog China 16.92
  3. CHINA_CHINA_6CH Village Dog China 17.01
  4. CHINA_CHINA_8CH Village Dog China 17.75
  5. CHINA_CHINA_7CH Village Dog China 18.22
CHINA_CHINA_4CH's breed

CHINA_CHINA_4CH pulls strongly toward the Golden Retriever cluster.

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.

  1. Golden Retriever 100%
Source

From the CanVAS (Spatola cohort) . Breed-page reference: Village Dog China.

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.

Body size
IGF1 C/C
HMGA2 C/T
SMAD2 A/G
LCORL G/G
STC2 C/C
ADAMTS17 G/A
Leg length
FGF4·CFA18 T/C
FGF4·CFA12 T/C
Coat
RSPO2 T/T
FGF5 T/C
KRT71 C/C
MC1R C/C
Ear set
MSRB3 G/A
Skull shape
BMP3 C/C
SMOC2 A/A
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.

UMAP-3D position
x -3.802
y 6.615
z 5.286
PCA-256 distance from breed centroid
11.91
Outlier percentile in breed
44
lower = more typical
Top-3 principal components by |z|

The 3 PCs on which CHINA_CHINA_4CH scores most extreme, with the 3 highest-loading SNPs on each. Foundation for the future genome-ring visualization.

PC46 z = 5.43
  • chr22:1,996,400 loading 0.0303
  • chr22:2,231,766 loading 0.0280
  • chr22:3,165,486 loading 0.0275
PC50 z = 2.91
  • chr22:2,473,315 loading 0.0334
  • chr22:1,969,643 loading -0.0326
  • chr4:32,946,669 loading -0.0320
PC31 z = -2.88
  • chr4:74,176,809 loading 0.0309
  • chr3:63,796,388 loading 0.0306
  • chr7:9,211,951 loading 0.0296
Ancestry reconstruction error: 0.20
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