qdecr: Run vertex-wise analyses
In slamballais/QDECR: Vertex-wise statistical analysis

Description Usage Arguments Details Value

Runs vertex-wise analyses using a variety of statistical models

qdecr(
  id,
  data,
  vertex = "qdecr",
  margs = NULL,
  model = c("stats::lm", "QDECR::megha", "RcppEigen::fastLm", "stats::glm",
    "survival::coxph", "default"),
  target = "fsaverage",
  hemi = c("lh", "rh"),
  measure = c("thickness", "area", "area.pial", "curv", "jacobian_white", "pial",
    "pial_lgi", "sulc", "volume", "w_g.pct", "white.H", "white.K"),
  fwhm = ifelse(measure == "pial_lgi", 5, 10),
  mcz_thr = 0.001,
  cwp_thr = 0.025,
  mgh = NULL,
  mask = NULL,
  mask_path = system.file("extdata", paste0(hemi, ".fsaverage.cortex.mask.mgh"),
    package = "QDECR"),
  project,
  dir_subj = Sys.getenv("SUBJECTS_DIR"),
  dir_fshome = Sys.getenv("FREESURFER_HOME"),
  dir_tmp = dir_out,
  dir_out,
  dir_out_tree = TRUE,
  file_out_tree = !dir_out_tree,
  clean_up = TRUE,
  clean_up_bm = TRUE,
  clobber = FALSE,
  verbose = TRUE,
  debug = FALSE,
  n_cores = 1,
  prep_fun = "prep_fastlm",
  analysis_fun = "analysis_chunkedlm",
  chunk_size = 1000
)

`id`	the name of the id variable that matches the dataset to the Freesurfer output
`data`	a required argument that contains a data frame, a list of data frames or an imputed object that is supported by the 'imp2list' function (mice, mi, etc.).
`vertex`	the preposition to the vertex measure (default: "qdecr_")
`margs`	the arguments that should be provided to the function of interest (e.g. stats::lm)
`model`	the function to grab the arguments from (this will be removed in a later version)
`target`	the target template (default = "fsaverage")
`hemi`	hemisphere to analyze ("lh" or "rh")
`measure`	the vertex-wise measure to use ("thickness", "area", etc.)
`fwhm`	full width half max (default = 10 mm, for pial_lgi it is 5 mm)
`mcz_thr`	A numeric value for the Monte Carlo simulation threshold (default: 0.001). Any of the following are accepted (equivalent values separate by '/'): 13/1.3/0.05, 20/2.0/0.01, 23/2.3/0.005, 30/3.0/0.001, 33/3.3/0.0005, 40/4.0/0.0001.
`cwp_thr`	the cluster-wise p-value threshold on top of all correction (default = 0.025, as there are 2 hemispheres)
`mgh`	NOT IMPLEMENTED; path to existing merged mgh file, default is NULL
`mask`	mgh file to mask analysis; default is to use the cortex label from the target
`mask_path`	path to the mask; default is the cortex mask that is provided with the QDECR package
`project`	the base name you want to assign to the output files
`dir_subj`	directory contain the surface-based maps (mgh files); defaults to SUBJECTS_DIR
`dir_fshome`	Freesurfer directory; defaults to FREESURFER_HOME
`dir_tmp`	directory to store the temporary big matrices; useful for shared memory; defaults to 'dir_out'
`dir_out`	the directory where to save the data to (defaults to the current directory)
`dir_out_tree`	if TRUE, creates a dir_out/project directory. If FALSE, all output is placed directory into dir_out
`file_out_tree`	if TRUE, adds the full project name to the output file names. By default it is the inverse of dir_out_tree
`clean_up`	NOT IMPLEMENTED; will be used for setting cleaning of other files
`clean_up_bm`	if TRUE, cleans all big matrices (.bk) that were generated in dir_tmp
`clobber`	if TRUE, ignores already existing directories and writes over them; if FALSE, stops and warns user that a given directory already exists
`verbose`	if TRUE, writes out standard log; if FALSE, no output is generated
`debug`	NOT IMPLEMENTED; will output the maximal log to allow for easy debugging
`n_cores`	the number of cores to be used
`prep_fun`	Name of the function that needs to be called for the preparation step (do not touch unless you know what you are doing!)
`analysis_fun`	Name of the function that needs to be called for the analysis step (do not touch unless you know what you are doing!)
`chunk_size`	Integer; the desired chunk size for the chunked lm

This function is the worker function of the QDECR package. It allows .mgh format data as input and allows statistical analyses per vertex. A variety of statistical models have been implemented, such as linear regression.

out

slamballais/QDECR documentation built on Jan. 9, 2022, 1:22 p.m.