brainGraph (version 3.1.0)

Creating_Graphs_GLM: Create a graph list with GLM-specific attributes

Description

These methods create a brainGraphList with attributes specific to the results of brainGraph_GLM, mtpc, or NBS. The graphs element of the returned object will contain one graph for each contrast.

Usage

# S3 method for bg_GLM
make_brainGraphList(x, atlas = x$atlas,
  type = "observed", level = "contrast", set.attrs = FALSE,
  modality = NULL, weighting = NULL, threshold = NULL,
  gnames = x$con.name, ...)
# S3 method for mtpc
make_brainGraphList(x, atlas = x$atlas,
  type = "observed", level = "contrast", set.attrs = FALSE,
  modality = NULL, weighting = NULL, threshold = NULL,
  gnames = x$con.name, ...)
# S3 method for NBS
make_brainGraphList(x, atlas, type = "observed",
  level = "contrast", set.attrs = TRUE, modality = NULL,
  weighting = NULL, threshold = NULL, gnames = x$con.name,
  mode = "undirected", weighted = TRUE, diag = FALSE, ...)

Value

A brainGraphList object, with a graph object for each contrast with additional attributes:

Graph

name (contrast name), outcome (the outcome variable), alpha (the significance level); for MTPC: tau.mtpc, S.mtpc, S.crit, A.crit

Vertex

size2 (t-statistic); size (the t-stat transformed for visualization purposes); p (equal to \(1-p\)); p.fdr (equal to \(1-p_{FDR}\), the FDR-adjusted p-value); effect.size (the contrast of parameter estimates for t-contrasts; the extra sum of squares for F-contrasts); se (the standard error of gamma); A.mtpc, sig (binary indicating whether A.mtpc > A.crit) (for MTPC)

make_brainGraphList.NBS returns graphs with additional attributes:

Vertex

comp (integer vector indicating connected component membership), p.nbs (P-value for each component)

Edge

stat (the test statistic for each connection), p (the P-value)

Arguments

x

A bg_GLM, mtpc, or NBS object

atlas

Character string specifying the brain atlas to use

type

Character string indicating the type of graphs. Default: observed

level

Character string indicating whether the graphs are subject-, group-, or contrast-specific. Default: 'subject'

set.attrs

Logical indicating whether to assign all graph-, vertex-, and edge-level attributes (via set_brainGraph_attr). Default: TRUE

modality

Character string indicating imaging modality (e.g. 'dti'). Default: NULL

weighting

Character string indicating how the edges are weighted (e.g., 'fa', 'pearson', etc.). Default: NULL

threshold

Integer or number indicating the threshold used when “sparsifying” the connectivity matrix (if any). Default: NULL

gnames

Character vector of graph names (e.g., study IDs if level='subject'). Default: NULL

...

Other arguments passed to set_brainGraph_attr

mode

Character string defining how the matrix should be interpreted. Default: 'undirected'

weighted

Logical specifying whether to create a weighted network

diag

Logical indicating whether to include the diagonal of the connectivity matrix. Default: FALSE

See Also

brainGraph_GLM, mtpc, NBS

Other Graph creation functions: Creating_Graphs, brainGraphList, make_ego_brainGraph