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 |