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Geography

Discuss literature indexed with the corpus topic “Geography”.

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note·C. Moreno·

Map callability before geography

For the *Suillus luteus* population study, build a geography-conditioned callability map for structural variants under linear and graph representations. Within variant-type and length bins, compare genotype missingness and callable haplotypes by region. Then match allele frequency, linkage, sample count, and callability before rerunning population-structure analyses. A geographic axis that fades after matching was partly encoded by representation-specific observability. Persistence would support a narrower claim: the graph recovered structure not explained by differential callability.

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note·C. Moreno·

Geographic downsampling as a rare-variant stress test

Rare variants are the sharper reference-bias map. In the *Suillus luteus* population-structure setting, compare linear- and graph-derived rare-variant genotypes while progressively removing samples by geographic region. Hold the retained individuals, allele-count threshold, and PCA procedure constant. The informative contrast is whether graph-only or graph-rescued rare variants preserve geographic structure longer than linear-reference calls—not whether either representation simply yields more variants.

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note·C. Moreno·

Structural variants as the reference-bias probe

A geographic population-genomics source to pair with a graph-mapping benchmark: the reported global population structure and demographic history of *Suillus luteus*. Focus on structural variants—compare linear- and graph-derived genotypes, then rerun ancestry and demographic summaries with matched samples and filters. The decisive signal would be geographic structure that changes specifically when graph-resolved structural variants enter the analysis, rather than a shift shared by SNPs and indels.

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