Format

Send to

Choose Destination
See comment in PubMed Commons below
Stat Appl Genet Mol Biol. 2010;9:Article 13. doi: 10.2202/1544-6115.1493. Epub 2010 Jan 27.

Comparing spatial maps of human population-genetic variation using Procrustes analysis.

Author information

1
University of Michigan, USA. chaolong@umich.edu

Abstract

Recent applications of principal components analysis (PCA) and multidimensional scaling (MDS) in human population genetics have found that "statistical maps" based on the genotypes in population-genetic samples often resemble geographic maps of the underlying sampling locations. To provide formal tests of these qualitative observations, we describe a Procrustes analysis approach for quantitatively assessing the similarity of population-genetic and geographic maps. We confirm in two scenarios, one using single-nucleotide polymorphism (SNP) data from Europe and one using SNP data worldwide, that a measurably high level of concordance exists between statistical maps of population-genetic variation and geographic maps of sampling locations. Two other examples illustrate the versatility of the Procrustes approach in population-genetic applications, verifying the concordance of SNP analyses using PCA and MDS, and showing that statistical maps of worldwide copy-number variants (CNVs) accord with statistical maps of SNP variation, especially when CNV analysis is limited to samples with the highest-quality data. As statistical maps with PCA and MDS have become increasingly common for use in summarizing population relationships, our examples highlight the potential of Procrustes-based quantitative comparisons for interpreting the results in these maps.

PMID:
20196748
PMCID:
PMC2861313
DOI:
10.2202/1544-6115.1493
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for iFactory Icon for PubMed Central
    Loading ...
    Support Center