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brainGraph (version 2.7.3)

import_scn: Import data for structural connectivity analysis

Description

Given a directory, atlas name, and modality, this function imports data for structural connectivity analysis. It expects files containing a table of region-wise structural MRI measures (e.g., mean cortical thickness), one for each hemisphere. The first column of all files should contain the subject ID; the column name will be changed to Study.ID.

Usage

import_scn(datadir, atlas, modality = "thickness", exclude.subs = NULL,
  custom.atlas = NULL)

Arguments

datadir

The path to the directory containing the data files

atlas

Character string specifying the atlas in use. For a custom atlas, please specify 'custom', and provide the name to the custom.atlas argument

modality

The structural imaging measure (default: 'thickness')

exclude.subs

Vector indicating the subjects to exclude, if any (default: NULL)

custom.atlas

Character string specifying the name of the R object for the atlas in use, if atlas='custom' was also supplied (default: NULL)

Value

A list containing:

atlas

Character string

modality

Character string

lhrh

A data.table of structural MRI measures for both hemispheres

aseg

A data.table of structural MRI measures for subcortical gray matter, if applicable

excluded

Vector of subject ID's that were excluded

missing

Vector of subject ID's that are not present in both the cortical and subcortical tables (if applicable)

Details

The files should have specific names; the second in the following list is only required for atlases/parcellations that include subcortical gray matter (e.g., dk.scgm).

  • ${parcellation}_${hemi}_${modality}.csv for cortical volume, thickness, surface area, or local gyrification index (LGI). Here, ${parcellation} can be aparc, aparc.DKTatlas40, or aparc.a2009s. For example, for cortical thickness with the Desikan-Killiany atlas, the filename should be aparc_lh_thickness.csv. If you are using a custom atlas, see the Note below. The ${hemi} variable is either lh or rh. Finally, ${modality} should be either volume, thickness, area, or lgi.

  • asegstats.csv for SCGM volume

See Also

Other Structural covariance network functions: Bootstrapping, IndividualContributions, Residuals, brainGraph_permute, corr.matrix, plot_volumetric

Examples

Run this code
# NOT RUN {
  raw_data <- import_scn('/home/cwatson/data', atlas='dkt',
                         exclude.subs=c('con07', 'con23', 'pat15'))
# }

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