 Équipes
 Productions scientifiques

 Séminaires
This program is dedicated to the estimation and the use of Drifting Markov Models (DMM).
SpM Estimation by splines M. N must be used.
SpH Estimation by splines H. N and Nar must be used.
Spl Estimation by splines. N and Nar must be used.
Poly Estimation by polynom (stochastic matrices).
PolyM Estimation by polynom (no stochastic matrices).
out <basename> Basename for all output files. Output 'basename.config_<num>.out' with s. Output 'basename.config_sm.out' with sm. Output 'basename.config_ss.out' with ss. Output 'basename.config.out' with cf.
a <alphabet_file> A file describing the alphabet to use.
s <sequence_file>A file containing file of sequences. DMM is estimated on each sequence (Use 1). At least one of s or sm or ss must be used
sm <sequence_mean_file> A file containing file of sequences. DMM is estimated as a mean of DDM on each sequence (Use 1). At least one of s or sm or ss must be used
ss <sequence_sum_file> A file containing file of sequences. DMM is estimated over all the sequences (Use 1). At least one of s or sm or ss must be used
order <order>=0>Order of the DMM (Use 1). Order must be > 0 with SpM or SpH.
deg <degree>=0> Degree of the DMM (Use 1). Degree is useless with SpH and Spl. Degree is 3.
N <Number of segments>0> Number of segments in the case of estimation by splines.
Nar <Number of segments>0> Number of aller retour with Spl and SpH.
cf <model_file> DMM is given by the <model_file> (Use 2). Must be used with Poly, PolyM, Spl, SpM, or SpH.
L Compute the loglikelihood on the estimated sequences (Use 1). Can not be used with sm or ss
AIC Compute the AIC on the estimated sequences (Use 1). Can not be used with sm or ss
BIC Compute the BIC on the estimated sequences (Use 1). Can not be used with sm or ss
l <sequence_file_l> Compute the loglikelihood on <sequence_file_l>.
aic <sequence_file_aic>Compute the aic on <sequence_file_aic>.
bic <sequence_file_bic> Compute the bic on <sequence_file_bic>.
law Compute the stationary law of the DMM. basename.trace_stat_<num>.out is an output containing the stationary law. <num> is an integer designing the number of the sequence.
slaw <in>0> <out>0> Compute the stationary law of the DMM between <in> and <out>. basename.trace_stat_segment_<num>.out is an output containing the stationary law. <num> is an integer designing the number of the sequence.
dist Compute distributions of the DMM. basename.trace_dist_<num>.out is an output containing the distributions. <num> is an integer designing the number of the sequence.
sdist <in>0> <out>0> Compute the distribution of the DMM between <in> and <out>. basename.trace_dist_segment_<num>.out is an output containing the distributions. <num> is an integer designing the number of the sequence.
pi Return files 'basename.Pit_<num>.out' or 'basename.Pit_sm.out' or basename.Pit.out' or 'basename.Pit_ss.out' containing the matrix Pi_t for all t. <num> is an integer designing the number of the sequence
simu Return files 'basename.simulation_<num>.out' or 'basename.simulation_sm.out' or 'basename.simulation_ss.out' or basename.simulation.out' containing a sequence simulated by the DMM. <num> is an integer designing the number of the sequence.
nv Mode 'not verbose'.
h Print this help.
DRIMM Poly order 1 deg 2 a dna.alpha s lambda.fa out lambda
for the estimation of a polynomial DMM (order 1 and degree 2) on the phage Lambda.
DRIMM SpM N 2 order 1 deg 3 a dna.alpha s lambda.fa out lambda
for the estimation of a DMM with polynomial splines (order 1 and degree 3 with 2 segments) on the phage Lambda.