corr.matrix {brainGraph}

Calculate correlation matrix and threshold

Description

corr.matrix calculates the correlation between all column pairs of a given data frame, and thresholds the resultant correlation matrix based on a given density (e.g., 0.1 if you want to keep only the 10% strongest correlations). If you want to threshold by a specific correlation coefficient (via the thresholds argument), then the densities argument is ignored.

The plot method will plot “heat maps” of the correlation matrices.

Usage

corr.matrix(resids, densities, thresholds = NULL, what = c("resids",
  "raw"), exclude.reg = NULL, type = c("pearson", "spearman"),
  rand = FALSE)

## S3 method for class 'corr_mats'
x[i, g = NULL]

## S3 method for class 'corr_mats'
plot(x, mat.type = c("thresholded", "raw"),
  thresh.num = 1L, ordered = TRUE, order.by = "lobe",
  graphs = NULL, grp.names = NULL, legend.title = NULL, ...)

## S3 method for class 'corr_mats'
region.names(object)

## S3 method for class 'corr_mats'
nregions(object)

Arguments

resids

An object of class brainGraph_resids (the output from get.resid)

densities

Numeric vector indicating the resultant network densities; keeps the top X% of correlations

thresholds

Numeric; absolute correlation value to threshold by (default: NULL)

what

Character string indicating whether to correlate the residuals or the raw structural MRI values (default: 'resids')

exclude.reg

Character vector of regions to exclude (default: NULL)

type

Character string indicating which type of correlation coefficient to calculate (default: 'pearson')

rand

Logical indicating whether the function is being called for permutation testing; not intended for general use (default: FALSE)

x, object

A corr_mats object

i

Integer for subsetting by density/threshold

g

Integer, character, or logical for subsetting by group

mat.type

Character string indicating whether to plot raw or thresholded (binarized) matrices. Default: 'raw'

thresh.num

Integer specifying which threshold to plot (if mat.type='thresholded'). Default: 1L

ordered

Logical indicating whether to order the vertices by some grouping. Default: TRUE

order.by

Character string indicating how to group vertices. Default: 'lobe'

graphs

A brainGraphList object containing graphs with the vertex-level attribute of interest. Default: NULL

grp.names

Character vector specifying the names of each group of vertices. Default: NULL

legend.title

Character string for the legend title. Default is to leave blank

...

Unused

Details

If you wish to exclude regions from your analysis, you can give the indices of their columns with the exclude.reg argument.

By default, the Pearson correlation coefficients are calculated, but you can return Spearman by changing the type argument.

Value

A corr_mats object containing the following components:

R, P

Numeric arrays of correlation coefficients and P-values. The length of the 3rd dimension equals the number of groups

r.thresh

A list of 3-d binary arrays indicating correlations that are above a certain threshold. The length of the list equals the number of groups, and the length of the 3rd dimension equals the number of thresholds/densities.

thresholds

Numeric matrix of the thresholds supplied. The number of columns equals the number of groups.

what

Residuals or raw values

exclude.reg

Excluded regions (if any)

type

Pearson or Spearman

atlas

The brain atlas used

densities

Numeric vector; the densities of the resulting graphs, if you chose to threshold each group to have equal densities.

Plotting correlation matrices

There are several ways to control the plot appearance. First, you may plot the “raw” correlations, or only those of the thresholded (binarized) matrices. Second, you may order the vertices by a given vertex attribute; by default, they will be ordered by lobe, but you may also choose to order by, e.g., network (for the dosenbach160 atlas) or by community membership. In the latter case, you need to pass a brainGraphList object to the graphs argument; each graph in the object must have a vertex attribute specified in order.by. Finally, you can control the legend text with grp.names.

Author(s)

Christopher G. Watson, [e-mail]

See Also

rcorr

Other Structural covariance network functions: Bootstrapping, IndividualContributions, Residuals, brainGraph_permute, import_scn, plot_volumetric

Examples

## Not run: 
myResids <- get.resid(lhrh, covars)
corrs <- corr.matrix(myResids, densities=densities)))

## End(Not run)
## Not run: 
corrs <- corr.matrix(myResids, densities)
plot(corrs, order.by='comm', graphs=g.list, grp.names='Community')

## End(Not run)