tigr-build-icm(1)


NAME

   tigr-glimmer --- Creates and outputs an interpolated Markov model(IMM)

SYNOPSIS

   tigr-build-icm

DESCRIPTION

   Program   build-icm.c  creates and outputs an interpolated Markov model
   (IMM) as described in the paper A.L. Delcher, D. Harmon, S.  Kasif,  O.
   White,  and S.L. Salzberg.  Improved Microbial Gene Identification with
   Glimmer.  Nucleic Acids Research, 1999,  in  press.   Please  reference
   this paper if you use the system as part of any published research.

   Input  comes from the file named on the command-line.  Format should be
   one string per line.  Each line has an  ID  string  followed  by  white
   space  followed  by  the  sequence  itself.   The  script  run-glimmer3
   generates an input file in  the  correct  format  using  the  'extract'
   program.

   The  IMM is constructed as follows: For a given context, say acgtta, we
   want to estimate the probability distribution of  the  next  character.
   We  shall  do  this as a linear combination of the observed probability
   distributions for this context and all of its  suffixes,  i.e.,  cgtta,
   gtta,  tta,  ta,  a  and  empty.   By observed distributions I mean the
   counts of the number of occurrences of these strings  in  the  training
   set.   The  linear combination is determined by a set of probabilities,
   lambda, one for each context string.  For  context  acgtta  the  linear
   combination coefficients are:

   lambda  (acgtta)  (1  -  lambda  (acgtta)) x lambda (cgtta) (1 - lambda
   (acgtta)) x (1 - lambda (cgtta)) x lambda (gtta) (1 - lambda  (acgtta))
   x (1 - lambda (cgtta)) x (1 - lambda (gtta)) x lambda (tta) (1 - lambda
   (acgtta)) x (1 - lambda (cgtta)) x (1 - lambda (gtta)) x  (1  -  lambda
   (tta))  x (1 - lambda (ta))  x (1 - lambda (a))

   We  compute  the  lambda  values  for each context as follows: - If the
   number  of  observations  in  the  training  set  is  >=  the  constant
   SAMPLE_SIZE_BOUND, the lambda for that context is 1.0 - Otherwise, do a
   chi-square test on the observations for this context  compared  to  the
   distribution  predicted  for  the one-character shorter suffix context.
   If the chi-square significance < 0.5, set the lambda for  this  context
   to  0.0  Otherwise  set  the  lambda  for  this context to: (chi-square
   significance) x (# observations) / SAMPLE_WEIGHT

   To run the program:

   build-icm <train.seq > train.model

   This will use the training  data  in  train.seq  to  produce  the  file
   train.model, containing your IMM.

SEE ALSO

   tigr-glimmer3   (1),   tigr-long-orfs   (1),   tigr-adjust  (1),  tigr-
   anomaly   (1), tigr-extract (1), tigr-check (1), tigr-codon-usage  (1),
   tigr-compare-lists  (1), tigr-extract (1), tigr-generate (1), tigr-get-
   len (1), tigr-get-putative (1),

   http://www.tigr.org/software/glimmer/

   Please see the readme in /usr/share/doc/tigr-glimmer for a  description
   on how to use Glimmer3.

AUTHOR

   This  manual  page  was  quickly  copied  from the glimmer web site and
   readme file  by  Steffen  Moeller  moeller@debian.org  for  the  Debian
   system.

                                                TIGR-GLIMMER     (1)   (1)





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