# Coordinate File (and T-Map) Group Difference

Determine if the differences between two groups of coordinate files are
statistically significant.

## Inputs

- Two groups of Coordinate files..
- Fiducial Coordinate file.
- Open Topology file.
- Area Correction metric/shape file.
- Area Correction metric/shape file column number.
- Number of Iterations. The number of iterations is limited
to pow(2, N).

- Positive Threshold.
- Alpha (p-value that ranges zero to one).

## Outputs

- Metric/Shape file containing the distances computed from the
input Coordinate files. This file contains one the distance and
the X/Y/Z distance components.
- Permutation Distance Metric/Shape file. This file contains
number of iterations columns.

- Paint file identifying clusters.
- Text report.

## Algorithm

- Create average coordinate files for both of the input groups.
- Compute deviations for both of the average coordinate
files. The deviations are derived from the distance between the
average coordinate and each of the individual's coordinates.
- (Coord Diff Only) Create the difference Metric/Shape file where
the first column is the distance between the two average coordinate
files and columns two, three, and four are the X/Y/Z distance
components.
- (T-Map Coord Diff Only) Create the difference Metric/Shape file
where first column is a T map where T = (distance between average
coords / (Average Coord 1 Deviation + Average Coord 2 Deviation)).
- Create a shuffled coordinate file where the number of columns is
the number of iterations entered by the user and use this shuffled
coordinate file to create the shuffled distance file.

- Find the biggest cluster in each column of the shuffled distance
file.
- Find the largest (alpha)(iterations) clusters in the shuffled
distance file and use this value as the cutoff in the distance file.
- Report all clusters and create the paint file showing the
clusters.