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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_gui | GUI for plotting graphs overlaid on an MNI152 image or in a circle |
| 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 |