MantelModTest function

Test single modularity hypothesis using Mantel correlation

Calculates the correlation and Mantel significance test between a hypothetical binary modularity matrix and a correlation matrix. Also gives mean correlation within- and between-modules. This function is usually only called by TestModularity.

MantelModTest(cor.hypothesis, cor.matrix, ...)

## Default S3 method:
MantelModTest(
  cor.hypothesis,
  cor.matrix,
  permutations = 1000,
  MHI = FALSE,
  ...,
  landmark.dim = NULL,
  withinLandmark = FALSE
)

## S3 method for class 'list'
MantelModTest(
  cor.hypothesis,
  cor.matrix,
  permutations = 1000,
  MHI = FALSE,
  landmark.dim = NULL,
  withinLandmark = FALSE,
  ...,
  parallel = FALSE
)

Arguments

• cor.hypothesis: Hypothetical correlation matrix, with 1s within-modules and 0s between modules.
• cor.matrix: Observed empirical correlation matrix.
• ...: additional arguments passed to MantelCor
• permutations: Number of permutations used in significance calculation.
• MHI: Indicates if Modularity Hypothesis Index should be calculated instead of AVG Ratio.
• landmark.dim: Used if permutations should be performed maintaining landmark structure in geometric morphometric data. Either 2 for 2d data or 3 for 3d data. Default is NULL for non geometric morphometric data.
• withinLandmark: Logical. If TRUE within-landmark correlation are used in calculation of correlation. Only used if landmark.dim is passed, default is FALSE.
• parallel: if TRUE computations are done in parallel. Some foreach back-end must be registered, like doParallel or doMC.

Returns

Returns a vector with the matrix correlation, significance via Mantel, within- and between module correlation.

Details

CalcAVG can be used when a significance test is not required.

Examples

# Create a single modularity hypothesis:
hypot = rep(c(1, 0), each = 6)
cor.hypot = CreateHypotMatrix(hypot)

# First with an unstructured matrix:
un.cor = RandomMatrix(12)
MantelModTest(cor.hypot, un.cor)

# Now with a modular matrix:
hypot.mask = matrix(as.logical(cor.hypot), 12, 12)
mod.cor = matrix(NA, 12, 12)
mod.cor[ hypot.mask] = runif(length(mod.cor[ hypot.mask]), 0.8, 0.9) # within-modules
mod.cor[!hypot.mask] = runif(length(mod.cor[!hypot.mask]), 0.3, 0.4) # between-modules
diag(mod.cor) = 1
mod.cor = (mod.cor + t(mod.cor))/2 # correlation matrices should be symmetric

MantelModTest(cor.hypot, mod.cor)

References

Porto, Arthur, Felipe B. Oliveira, Leila T. Shirai, Valderes Conto, and Gabriel Marroig. 2009. "The Evolution of Modularity in the Mammalian Skull I: Morphological Integration Patterns and Magnitudes." Evolutionary Biology 36 (1): 118-35. doi:10.1007/s11692-008-9038-3.

Modularity and Morphometrics: Error Rates in Hypothesis Testing Guilherme Garcia, Felipe Bandoni de Oliveira, Gabriel Marroig bioRxiv 030874; doi: http://dx.doi.org/10.1101/030874

See Also

mantel,MantelCor,CalcAVG,TestModularity

Author(s)

Diogo Melo, Guilherme Garcia