Package index • verywise

All functions

as.mgh(): Create an object structured like an MGH object
barnard.rubin(): Pooled degrees of freedom calculation
build_supersubject(): Build "supersubject" by stacking all vertex data in one large file-backed matrix with dimensions n_subjects x n_vertices.
check_pheno_obj(): Check that object exists in the global environment
chunk_Ymats(): Compute the sum and sum of squares of Y
compress_local(): Compress a site's results into a tar.gz archive
compute_clusters(): Compute significant clusters of vertices
convert_to_mgh(): Convert statistical result FBMs to FreeSurfer .mgh format
create_cortex_mask(): @title Save logical cortex mask from FreeSurfer cortex.label files
estimate_fwhm(): Estimate full-width half maximum (FWHM)
fbm2mgh(): Save file backed matrix (FBM) to MGH file
fbm_col_has_0(): Check if all row elements are 0 in FBM
imp2list(): Convert imputation object to a list of dataframes
init_progress_tracker(): Initialize per-chunk progress tracking
list.dirs.till(): List sub-directories till depth n
load.mgh(): Load an MGH file into memory
load_pheno_file(): Load "phenotype" file into R based on its extension
locate_roi(): Locate vertices belonging to specific cortical ROIs
make_chunk_sequence(): Define chunks of vertices for analyses
mask_cortex(): Clean out vertices that are not on the cortex
move_result_files(): Move key result files from one directory to another (for sharing and visualization)
plot_vw_map(): Plot vertex-wise coefficient maps on a 3D cortical surface
prettify_message(): Print pretty messages to console
run_voxw_lmm(): Run voxel-wise linear mixed model using lme4::lmer()
run_vw_fed_aggr(): Run federated aggregation for vertex-wise distributed LMM
run_vw_fed_local(): Run vertex-wise linear model on local site data
run_vw_lmm(): Run vertex-wise linear mixed model using lme4::lmer()
run_vw_meta(): Vertex-wise Random-Effects Meta-Analysis Across Studies
save.mgh(): Save an MGH file from memory
significant_cluster_stats(): Calculate Significant Cluster Statistics
simulate_distrib_dataset(): Simulate a distributed (multi-site) cross-sectional brain surface dataset
simulate_freesurfer_data(): Simulate longitudinal FreeSurfer vertex-wise data
simulate_long_pheno_data(): Simulate (longitudinal) phenotype data
simulate_longit_dataset(): Simulate a longitudinal brain surface dataset with associated phenotype data
single_lmm(): Run a single linear mixed model and extract statistics
subset_supersubject(): Subset an existing supersubject matrix by matching folder IDs
unpack_formula(): Unpack R formula
update_progress_tracker(): Update within-chunk progress for a (milestone) vertex
vw_message(): Print message to console if verbose = TRUE
vw_pool(): Pool lme4::lmer model output across imputed datasets
vw_pretty_message(): Print decorated message to console if verbose = TRUE
with_parallel(): Run a chunked foreach loop sequentially or in parallel