# Graph Theory Analysis of Brain MRI Data

## Documentation for package ‘brainGraph’ version 3.1.1

- DESCRIPTION file
- Package NEWS

## Help Pages

A B C D E F G H I L M N P Q R S T V W X misc

brainGraph-package | Default options for brainGraph

## -- A --

aal116 | Coordinates for data from brain atlases
aal2.120 | Coordinates for data from brain atlases
aal2.94 | Coordinates for data from brain atlases
aal90 | Coordinates for data from brain atlases
analysis_random_graphs | Perform an analysis with random graphs for brain MRI data
anova.bg_GLM | Extract model fit statistics from a bg_GLM object
aop | Approaches to estimate individual network contribution
apply_thresholds | Threshold additional set of matrices
as_atlas | Atlas helper functions
as_brainGraphList | Create a list of brainGraph graphs
Atlas Helpers | Atlas helper functions
Attributes | Set graph, vertex, and edge attributes common in MRI analyses

## -- B --

bg_to_mediate | Mediation analysis with brain graph measures as mediator variables
Bootstrapping | Bootstrapping for global graph measures
Brain Atlases | Coordinates for data from brain atlases
brainGraph | Default options for brainGraph
brainGraph-methods | brainGraph generic methods
brainGraph-options | Default options for brainGraph
brainGraphList | Create a list of brainGraph graphs
brainGraph_boot | Bootstrapping for global graph measures
brainGraph_GLM | Fit General Linear Models at each vertex of a graph
brainGraph_GLM_design | Create a design matrix for linear model analysis
brainGraph_mediate | Mediation analysis with brain graph measures as mediator variables
brainGraph_permute | Permutation test for group difference of graph measures
brainnetome | Coordinates for data from brain atlases
brainsuite | Coordinates for data from brain atlases

## -- C --

case.names.bg_GLM | Extract basic information from a bg_GLM object
case.names.brainGraph_resids | Linear model residuals in structural covariance networks
case.names.mtpc | Multi-threshold permutation correction
case.names.NBS | Network-based statistic for brain MRI data
centr_betw_comm | Calculate communicability betweenness centrality
centr_lev | Calculate a vertex's leverage centrality
check_sID | Test if an object is a character vector of numbers
coef.bg_GLM | Extract model fit statistics from a bg_GLM object
coeff_determ | Extract model fit statistics from a bg_GLM object
coeff_table | Extract model fit statistics from a bg_GLM object
coeff_var | Calculate coefficient of variation
coeff_var.default | Calculate coefficient of variation
colMax | Matrix/array utility functions
colMaxAbs | Matrix/array utility functions
colMin | Matrix/array utility functions
communicability | Calculate communicability
confint.bg_GLM | Extract model fit statistics from a bg_GLM object
contract_brainGraph | Contract graph vertices based on brain lobe and hemisphere
cooks.distance.bg_GLM | Influence measures for a bg_GLM object
cor.diff.test | Calculate the p-value for differences in correlation coefficients
corr.matrix | Calculate correlation matrix and threshold
Count Edges | Count number of edges of a brain graph
count_homologous | Count number of edges of a brain graph
count_inter | Count number of edges of a brain graph
covratio.bg_GLM | Influence measures for a bg_GLM object
craddock200 | Coordinates for data from brain atlases
create_atlas | Atlas helper functions
create_mats | Create connection matrices for tractography or fMRI data
Creating_Graphs | Create a brainGraph object
Creating_Graphs_GLM | Create a graph list with GLM-specific attributes

## -- D --

destrieux | Coordinates for data from brain atlases
destrieux.scgm | Coordinates for data from brain atlases
deviance.bg_GLM | Extract model fit statistics from a bg_GLM object
df.residual.bg_GLM | Extract model fit statistics from a bg_GLM object
df.residual.mtpc | Multi-threshold permutation correction
df.residual.NBS | Network-based statistic for brain MRI data
dfbeta.bg_GLM | Influence measures for a bg_GLM object
dfbetas.bg_GLM | Influence measures for a bg_GLM object
dffits.bg_GLM | Influence measures for a bg_GLM object
diag_sq | Matrix/array utility functions
dk | Coordinates for data from brain atlases
dk.scgm | Coordinates for data from brain atlases
dkt | Coordinates for data from brain atlases
dkt.scgm | Coordinates for data from brain atlases
dosenbach160 | Coordinates for data from brain atlases

## -- E --

edge_asymmetry | Calculate an asymmetry index based on edge counts
edge_spatial_dist | Calculate Euclidean distance of edges and vertices
efficiency | Calculate graph global, local, or nodal efficiency
Extract.brainGraphList | Create a list of brainGraph graphs
Extract.brainGraph_resids | Linear model residuals in structural covariance networks
Extract.corr_mats | Calculate correlation matrix and threshold
extractAIC.bg_GLM | Model selection for bg_GLM objects

## -- F --

fastLmBG | Fit design matrices to one or multiple outcomes
fastLmBG_3d | Fit design matrices to one or multiple outcomes
fastLmBG_3dY | Fit design matrices to one or multiple outcomes
fastLmBG_3dY_1p | Fit design matrices to one or multiple outcomes
fastLmBG_f | Fit design matrices to one or multiple outcomes
fastLmBG_t | Fit design matrices to one or multiple outcomes
fitted.bg_GLM | Extract model fit statistics from a bg_GLM object
formula.bg_GLM | Extract basic information from a bg_GLM object
formula.mtpc | Multi-threshold permutation correction
formula.NBS | Network-based statistic for brain MRI data

## -- G --

gateway_coeff | Gateway coefficient, participation coefficient, and within-mod degree z-score
get.resid | Linear model residuals in structural covariance networks
get_thresholds | Matrix/array utility functions
GLM | Fit General Linear Models at each vertex of a graph
GLM basic info | Extract basic information from a bg_GLM object
GLM design | Create a design matrix for linear model analysis
GLM fits | Fit design matrices to one or multiple outcomes
GLM influence measures | Influence measures for a bg_GLM object
GLM model selection | Model selection for bg_GLM objects
GLM statistics | Extract model fit statistics from a bg_GLM object
gordon333 | Coordinates for data from brain atlases
Graph Data Tables | Create a data table with graph global and vertex measures
Graph Distances | Calculate Euclidean distance of edges and vertices
graph_attr_dt | Create a data table with graph global and vertex measures
groups.brainGraphList | brainGraph generic methods
groups.brainGraph_resids | Linear model residuals in structural covariance networks
groups.corr_mats | brainGraph generic methods
guess_atlas | Atlas helper functions

## -- H --

hatvalues.bg_GLM | Influence measures for a bg_GLM object
hcp_mmp1.0 | Coordinates for data from brain atlases
hoa112 | Coordinates for data from brain atlases
hubness | Calculate vertex hubness

## -- I --

import_scn | Import data for structural connectivity analysis
IndividualContributions | Approaches to estimate individual network contribution
influence.bg_GLM | Influence measures for a bg_GLM object
inv | Calculate the inverse of the cross product of a design matrix
inv.array | Calculate the inverse of the cross product of a design matrix
inv.list | Calculate the inverse of the cross product of a design matrix
inv.matrix | Calculate the inverse of the cross product of a design matrix
inv.qr | Calculate the inverse of the cross product of a design matrix
Inverse | Calculate the inverse of the cross product of a design matrix
is.brainGraph | Create a brainGraph object
is.brainGraphList | Create a list of brainGraph graphs
is_binary | Matrix/array utility functions

## -- L --

labels.bg_GLM | Extract basic information from a bg_GLM object
labels.mtpc | Multi-threshold permutation correction
labels.NBS | Network-based statistic for brain MRI data
logLik.bg_GLM | Model selection for bg_GLM objects
loo | Approaches to estimate individual network contribution
lpba40 | Coordinates for data from brain atlases

## -- M --

make_auc_brainGraph | Calculate the AUC across densities of given attributes
make_brainGraph | Create a brainGraph object
make_brainGraph.bg_mediate | Create a brainGraph object
make_brainGraph.igraph | Create a brainGraph object
make_brainGraph.matrix | Create a brainGraph object
make_brainGraphList | Create a list of brainGraph graphs
make_brainGraphList.array | Create a list of brainGraph graphs
make_brainGraphList.bg_GLM | Create a graph list with GLM-specific attributes
make_brainGraphList.corr_mats | Create a list of brainGraph graphs
make_brainGraphList.mtpc | Create a graph list with GLM-specific attributes
make_brainGraphList.NBS | Create a graph list with GLM-specific attributes
make_ego_brainGraph | Create a graph of the union of multiple vertex neighborhoods
make_empty_brainGraph | Create a brainGraph object
make_intersection_brainGraph | Create the intersection of graphs based on a logical condition
Matrix utilities | Matrix/array utility functions
mean_distance_wt | Calculate weighted shortest path lengths
Mediation | Mediation analysis with brain graph measures as mediator variables
mtpc | Multi-threshold permutation correction

## -- N --

NBS | Network-based statistic for brain MRI data
nobs.bg_GLM | Extract basic information from a bg_GLM object
nobs.brainGraphList | Create a list of brainGraph graphs
nobs.brainGraph_resids | Linear model residuals in structural covariance networks
nobs.mtpc | Multi-threshold permutation correction
nobs.NBS | Network-based statistic for brain MRI data
nregions | brainGraph generic methods
nregions.bg_GLM | Extract basic information from a bg_GLM object
nregions.brainGraph_resids | Linear model residuals in structural covariance networks
nregions.corr_mats | Calculate correlation matrix and threshold
nregions.mtpc | Multi-threshold permutation correction
nregions.NBS | Network-based statistic for brain MRI data

## -- P --

pad_zeros | Test if an object is a character vector of numbers
partition | GLM non-parametric permutation testing
part_coeff | Gateway coefficient, participation coefficient, and within-mod degree z-score
pinv | Calculate the inverse of the cross product of a design matrix
plot.bg_GLM | Fit General Linear Models at each vertex of a graph
plot.brainGraph | Plot a brain graph with a specific spatial layout
plot.brainGraphList | Plot a brainGraphList and write to PDF
plot.brainGraph_boot | Bootstrapping for global graph measures
plot.brainGraph_GLM | Plot a graph with results from GLM-based analyses
plot.brainGraph_mediate | Plot a graph with results from GLM-based analyses
plot.brainGraph_mtpc | Plot a graph with results from GLM-based analyses
plot.brainGraph_NBS | Plot a graph with results from GLM-based analyses
plot.brainGraph_permute | Permutation test for group difference of graph measures
plot.brainGraph_resids | Linear model residuals in structural covariance networks
plot.corr_mats | Calculate correlation matrix and threshold
plot.IC | Approaches to estimate individual network contribution
plot.mtpc | Multi-threshold permutation correction
Plotting GLM graphs | Plot a graph with results from GLM-based analyses
plot_brainGraph_multi | Save PNG of one or three views for all graphs in a brainGraphList
plot_global | Plot global graph measures across densities
plot_rich_norm | Plot normalized rich club coefficients against degree threshold
plot_vertex_measures | Plot vertex-level graph measures at a single density or threshold
plot_volumetric | Plot group distributions of volumetric measures for a given brain region
power264 | Coordinates for data from brain atlases
print.bg_GLM | Fit General Linear Models at each vertex of a graph
print.brainGraphList | Create a list of brainGraph graphs

## -- Q --

qr.array | Matrix/array utility functions
qr_Q2 | Matrix/array utility functions
qr_R2 | Matrix/array utility functions

## -- R --

Random Graphs | Perform an analysis with random graphs for brain MRI data
randomise | GLM non-parametric permutation testing
randomise_3d | GLM non-parametric permutation testing
region.names | brainGraph generic methods
region.names.bg_GLM | Extract basic information from a bg_GLM object
region.names.brainGraph_resids | Linear model residuals in structural covariance networks
region.names.corr_mats | Calculate correlation matrix and threshold
region.names.data.table | brainGraph generic methods
region.names.mtpc | Multi-threshold permutation correction
Residuals | Linear model residuals in structural covariance networks
residuals.bg_GLM | Extract model fit statistics from a bg_GLM object
Rich Club | Rich club calculations
rich_club_all | Rich club calculations
rich_club_attrs | Assign graph attributes based on rich-club analysis
rich_club_coeff | Rich club calculations
rich_club_norm | Rich club calculations
rich_core | Rich club calculations
robustness | Analysis of network robustness
rstandard.bg_GLM | Influence measures for a bg_GLM object
rstudent.bg_GLM | Influence measures for a bg_GLM object

## -- S --

set_brainGraph_attr | Set graph, vertex, and edge attributes common in MRI analyses
sigma.bg_GLM | Extract model fit statistics from a bg_GLM object
sim.rand.graph.clust | Perform an analysis with random graphs for brain MRI data
sim.rand.graph.hqs | Perform an analysis with random graphs for brain MRI data
sim.rand.graph.par | Perform an analysis with random graphs for brain MRI data
slicer | Save PNG of one or three views for all graphs in a brainGraphList
small.world | Calculate graph small-worldness
summary.bg_GLM | Fit General Linear Models at each vertex of a graph
summary.bg_mediate | Mediation analysis with brain graph measures as mediator variables
summary.brainGraph | Create a brainGraph object
summary.brainGraph_boot | Bootstrapping for global graph measures
summary.brainGraph_permute | Permutation test for group difference of graph measures
summary.brainGraph_resids | Linear model residuals in structural covariance networks
summary.IC | Approaches to estimate individual network contribution
summary.mtpc | Multi-threshold permutation correction
summary.NBS | Network-based statistic for brain MRI data
symmetrize | Matrix/array utility functions
symmetrize.array | Matrix/array utility functions
symmetrize.matrix | Matrix/array utility functions
symm_mean | Matrix/array utility functions
s_core | Calculate the s-core of a network

## -- T --

terms.bg_GLM | Extract basic information from a bg_GLM object
terms.mtpc | Multi-threshold permutation correction
terms.NBS | Network-based statistic for brain MRI data

## -- V --

variable.names.bg_GLM | Extract basic information from a bg_GLM object
variable.names.mtpc | Multi-threshold permutation correction
variable.names.NBS | Network-based statistic for brain MRI data
vcov.bg_GLM | Extract model fit statistics from a bg_GLM object
Vertex Roles | Gateway coefficient, participation coefficient, and within-mod degree z-score
vertex_attr_dt | Create a data table with graph global and vertex measures
vertex_spatial_dist | Calculate Euclidean distance of edges and vertices
vif.bg_GLM | Variance inflation factors for 'bg_GLM' objects
vulnerability | Calculate graph vulnerability

## -- W --

within_module_deg_z_score | Gateway coefficient, participation coefficient, and within-mod degree z-score
write_brainnet | Write files to be used for visualization with BrainNet Viewer

## -- X --

xfm.weights | Set graph, vertex, and edge attributes common in MRI analyses

## -- misc --

[.bg_GLM | Fit General Linear Models at each vertex of a graph
[.brainGraphList | Create a list of brainGraph graphs
[.brainGraph_resids | Linear model residuals in structural covariance networks
[.corr_mats | Calculate correlation matrix and threshold