This function runs a vertex-wise random-effects meta-analysis across multiple
studies (sites or cohorts). Is expects individual study results as they are
outputted but verywise::run_vw_lmm or by QDECR.
Usage
run_vw_meta(
term,
hemi = c("lh", "rh"),
measure = "area",
res_dirs,
study_names,
fs_template = "fsaverage",
n_cores = 1,
verbose = TRUE
)Arguments
- term
Character. Name of the model term to visualize (matches entries in
stack_names.txt).- hemi
Character. Hemisphere to analyse (
"lh"or"rh").- measure
Character. Surface measure, e.g.
'area','thickness','volume'. Defaults to'area'.- res_dirs
Character vector. Path to the directories containing vertex-wise result files (
*.mgh) of each study.- study_names
Character vector of study names (must match the length of
res_dirs).- fs_template
Character string specifying the FreeSurfer template surface. The following values are accepted:
fsaverage (default) = 163842 vertices (highest resolution),
fsaverage6 = 40962 vertices,
fsaverage5 = 10242 vertices,
fsaverage4 = 2562 vertices,
fsaverage3 = 642 vertices
- n_cores
Integer. Number of CPU cores to use for parallel processing (default: 1).
- verbose
Logical. verbose execution (default: TRUE)
Value
A named list with three FBM objects:
- coef
Meta-analytic effect size estimates at each vertex.
- se
Meta-analytic standard errors at each vertex.
- p
Meta-analytic p-values at each vertex.
Additionally, these are exported as MGH files in the working directory.
Details
For each vertex, the function loads the effect size and standard error from each study, computes the variance,
and runs a random-effects meta-analysis using rma. Results are saved as
Filebacked Big Matrices (FBM) and as MGH files for downstream neuroimaging analysis.