Subtyping pipeline

Overview of the subtyping pipeline

The goal of this pipeline is to cluster subjects together based on similarity on a given measure (e.g. functional connectivity, cortical thickness, etc) and then perform subsequent statistical analyses.

The steps of the pipeline are as follows:

• Preprocessing of the data to create a "stack" map as input for the rest of the pipeline, with the option of regressing confounds prior to subtyping. The stack map contains a Subjects x Voxels x Networks array. See niak_brick_network_stack.m for more info.
• Generating the similarity matrix, a Subjects x Subjects matrix to illustrate how similar subjects are to one another and how subjects can be clustered together. See niak_brick_similarity_matrix.m for more info.
• Clustering the subjects to form subtypes (or subgroups) within the dataset See niak_brick_subtyping.m for more info.
• Calculating the subtype "weights" for each subject, a measure of the strength of the association between each subject to a given subtype. See niak_brick_subtype_weight.m for more info.
• Statistical tests of association, to test how subtypes may be related to variables of interest. See niak_brick_association_test.m for more info.

Input files

• Individual maps (e.g. rmap_part, stability_maps, etc). N.B. Assumes there is only one (1) mnc.gz or nii.gz per subject.
• A 3D binary mask
• A model file (.csv): A .csv file containing demographic information for each subject, including variables of interest and confound variables