TIGR-GLIMMER	 (1)   (1)				      General Commands Manual					TIGR-GLIMMER	 (1)   (1)

NAME

       tigr-glimmer -- Ceates 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  refer-
       ence 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 combi-
       nation 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  SAM-
       PLE_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)