Boulder Laboratory for 3-Dimensional Electron Microscopy of Cells

SUBIMANOVA(1)							 SUBIMANOVA(1)

NAME
	subimanova - subtracts image averages with analysis of variance

SYNOPSIS
	subimanova

DESCRIPTION

  SUBIMANOVA subtracts one set of average images from another set and
  uses a nested analysis of variance (ANOVA) to find the statistical
  significance of the difference at each pixel.  It then sets to zero
  all differences less significant than a specified level.  The program
  can output either actual differences or pixel values that reflect
  the level of significance.  In order to do the ANOVA, it must have a
  standard deviation or variance image corresponding to each average
  image.
  
  The average and standard deviation/variance images can be ones
  produced by IMAVGSTAT or by other means.  When one starts the
  program, one designates a pair of A files (with average and S.D./VAR
  images) and a pair of B files.  One can then subtract any set of
  sections in B from any set of sections in A; A and B may be the same
  pair of files.
  
  The user is responsible for keeping track of how many samples were
  used in making each average, and informing this program of those
  numbers.  The program needs these numbers to do the ANOVA.
  
  Entries to the program:
  
  Average image file A
  Standard deviation or variance image file A
  Average image file B, or Return if same as file for A
  Standard deviation or variance image file B, or Return if same as
     file for A
  Output image file to store differences in
  
  0 to use a simple mean when combining the average images of one set,
     or 1 to form a weighted mean, where each average image would be
     weighted by the number of samples combined to form that average.
     In the latter case, the mean would be identical to the average
     image that could be obtain by combining ALL of the samples of
     that set.

  0 if the files have standard deviations in them, or 1 if the files
     have variances

  Number of differences to compute
  
  For each difference, enter:

     List of section numbers in file A, where ranges are allowed
        (e.g. 0-2,4,7-8).

     List of section numbers in file B, where ranges are allowed

     Number of samples making up those averages for each section in A

     Number of samples making up those averages for each section in B

     Significance level (e.g. 0.05, 0.01, etc).  Differences with less
        than this significance will be set to zero.  Enter a
        negative value to have significant pixels values set to 
        the negative of the log of the probability, or to the positive
        log for negative differences.  For example, positive and
        negative differences with a P of 0.01 would be output as
        2 and -2, respectively.

  
  The infamous Satterthwaite approximation will be used whenever the
  criteria for its application are satisfied.  An entry to make this
  optional is commented out in the code below.

HISTORY
  Written by David Mastronarde,  4/23/90
  4/12/95 changed to use local subroutines instead of NAG ones