This is the command tigr-build-icm that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator
PROGRAM:
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 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.
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