AFNI program: 3dFDR

Program:          3dFDR 
Author:           B. Douglas Ward 
Initial Release:  31 January 2002 
Latest Revision:  31 January 2002 

This program implements the False Discovery Rate (FDR) algorithm for       
thresholding of voxelwise statistics.                                      
                                                                           
Program input consists of a functional dataset containing one (or more)    
statistical sub-bricks.  Output consists of a bucket dataset with one      
sub-brick for each input sub-brick.  For non-statistical input sub-bricks, 
the output is a copy of the input.  However, statistical input sub-bricks  
are replaced by their corresponding FDR values, as follows:                
                                                                           
For each voxel, the minimum value of q is determined such that             
                               E(FDR) <= q                                 
leads to rejection of the null hypothesis in that voxel. Only voxels inside
the user specified mask will be considered.  These q-values are then mapped
to z-scores for compatibility with the AFNI statistical threshold display: 
                                                                           
               stat ==> p-value ==> FDR q-value ==> FDR z-score            
                                                                           
Usage:                                                                     
  3dFDR                                                                    
    -input fname       fname = filename of input 3d functional dataset     
      OR                                                                   
    -input1D dname     dname = .1D file containing column of p-values      
                                                                           
    -mask_file mname   Use mask values from file mname.                    
                       Note: If file mname contains more than 1 sub-brick, 
                       the mask sub-brick must be specified!               
                       Default: No mask                                    
                                                                           
    -mask_thr m        Only voxels whose corresponding mask value is       
                       greater than or equal to m in absolute value will   
                       be considered.  Default: m=1                        
                                                                           
                       Constant c(N) depends on assumption about p-values: 
    -cind              c(N) = 1   p-values are independent across N voxels 
    -cdep              c(N) = sum(1/i), i=1,...,N   any joint distribution 
                       Default:  c(N) = 1                                  
                                                                           
    -quiet             Flag to suppress screen output                      
                                                                           
    -list              Write sorted list of voxel q-values to screen       
                                                                           
    -prefix pname      Use 'pname' for the output dataset prefix name.     
      OR                                                                   
    -output pname                                                          
                                                                           


INPUT DATASET NAMES
-------------------
This program accepts datasets that are modified on input according to the
following schemes:
  'r1+orig[3..5]'                                    {sub-brick selector}
  'r1+orig<100.200>'                                 {sub-range selector}
  'r1+orig[3..5]<100..200>'                          {both selectors}
  '3dcalc( -a r1+orig -b r2+orig -expr 0.5*(a+b) )'  {calculation}
For the gruesome details, see the output of 'afni -help'.