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Mantel tests are used to reject the absence of correlation between a matrix of genetic distances and a matrix of linguistic distances, and do not require reconstructing population trees.
PLS finds a quantitative relationship between a matrix of independent variables X and one or several response variables (y vector or matrix) by simultaneously projecting X and y to latent structures (PLS components) [29].
To examine the pattern of isolation by distance we tested the correlation between a matrix of pairwise F ST / 1- F ST) values among localities and a matrix of the natural log of Euclidean geographic distances between localities.
A Mantel test of the correlation between a matrix of geographic distances (Table 6) and F ST values among localities was not significant (P = 0.629), suggesting that factors other than mere isolation-by-distance are responsible for the observed genetic structure.
Indeed, Mantel statistics (r) are high and significant when spatial autocorrelation is explicitly tested, i.e., when testing the association between a matrix of genetic distance and a matrix of geographic distance (avr Rvi6: r = 0.14, p < 0.01; vir Rvi6: r = 0.15, p < 0.001; first three rows in Additional file 1: Table S5).
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The nestin- and TUBB3-positive cells are positioned on top or in between of a matrix of flattened polyhedral cells.
The possible regulatory interactions between such a matrix of four human genes, three cis-NATs and two trans-NATs seems complex.
As a measure of genetic distance between populations, a matrix of co-ancestry coefficients was estimated in Arlequin 2.0 [ 57], which considers pair-wise distance, population size and divergence time.
The Correlation view represents Pearson-correlation coefficients and relationships between variables as a matrix of scatter plots and values.
The evaluation process looks for the best match between the abundance images produced by the unmixing and the image regions identified with each class in the ground truth.f We compute all the possible spatial correlations between them, obtaining a matrix of correlation indices.
To assess the association levels of the expression datasets (RPKM) between time periods, a matrix of similarity was calculated using the Pearson correlation coefficient (Fig. 6).
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