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 |

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 |

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 |

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 |

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 |

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 |

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 |

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 |

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 |

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 |

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 |

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 |

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 |

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 |

qr.array | Matrix/array utility functions |

qr_Q2 | Matrix/array utility functions |

qr_R2 | Matrix/array utility functions |

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 |

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 |

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 |

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 |

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 |

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

[.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 |