viterbi: viterbi

In gowachin/BeeMarkov:

Description

Compute a data.frame explaining loglikelyhood of every base of a sequence with a Viterbi algorithme based of a model of transition between 2 different models. These models are trained with 2 differents datasets.

Usage

viterbi(file, pos_training = "raw_data/mus_cpg_app.fa",
  neg_training = "raw_data/mus_tem_app.fa", l_word_pos = 1,
  l_word_neg = 1, n_train = 1160, n_ana = 1, l_c = 1000,
  l_nc = 125000)

Arguments

file	a file (fasta) to read and to run viterbi on
pos_training	a file (fasta) to read and train the positive model
neg_training	a file (fasta) to read and train the negative model
l_word_pos	a value for lengths of words for the model. Equal to the "order of the model + 1"
l_word_neg	a value fof lengths of words for the model. Equal to the "order of the model + 1"
n_train	number of sequences to train with
n_ana	number of sequences to analyse
l_c	mean length of a CpG+ region
l_nc	mean length of a CpG- region

Author(s)

Jaunatre Maxime <[e-mail]>

gowachin/BeeMarkov documentation built on Dec. 1, 2019, 2:57 a.m.