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Before running The Connectome Analyzer
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Input format
------------

One matrix per subject is required. Currently, the Connectome Analyzer supports csv files and matlab ".mat" files containing the data in a "matrix" variable.

The connectivity matrices can summarize connectivity measurements from any source (structural, functional, EEG, etc...). However, the matrices should all be the representation of an undirected (weighted or unweighted) graph, with the same dimensions across all subjects.

Data organization
-----------------

Group studies
.............

The Connectome Analyzer is mainly intended to test for statistical differences between the connectivity matrices of two groups. For this kind of analysis, your project organization should contain two folders, one called "Group1" and a second one called "Group2", each one containing its respective set of files (no particular nomenclature for the file name is required)::

	├── Project_directory
	│ │
	│ ├── Group1
	│ │ │
	│ │ ├── file_for_Subj1
	│ │ ├── file_for_Subj2
	│ │ ├── file_for_Subj3
	│ │ ├── ...
	│ │ └── file_for_SubjN
	│ │
	│ └── Group2
	│   │
	│   ├── file_for_Subj1
	│   ├── file_for_Subj2
	│   ├── file_for_Subj3
	│   ├── ...
	│   └── file_for_SubjM
	│
       ...

.. note::
	If you want to perform feature regression, like age or gender, each connectivity matrix should have a unique filename (ie subject1 in Group1 can not have the same filename as subject1 in Group2 or any other subject)

Single file analysis
....................

The Connectome Analyzer also provides tools to analyse single subject network metrics, or to apply the relaxation method to a matrix of p-values. In this case only one input file is required without any folder special organization.