hmm                package:VanillaICE                R Documentation

_F_i_t_s _h_i_d_d_e_n _M_a_r_k_o_v _m_o_d_e_l_s _t_o _h_i_g_h _t_h_r_o_u_g_h_p_u_t _S_N_P _c_h_i_p _d_a_t_a.

_D_e_s_c_r_i_p_t_i_o_n:

     Fits a hidden Markov model to high throughput SNP chip data

_U_s_a_g_e:

     hmm(object, ...)

_A_r_g_u_m_e_n_t_s:

  object: an object extending 'hSet'

     ...: See details

_D_e_t_a_i_l_s:

     *  verbose:  if TRUE, print information about the processing

     *  log2: if TRUE, a log2 transformation of copy number estimates
        is performed prior to fitting the hmm.

     *  arm: which arm of the chromosome to fit the hidden markov model
        (p, q, or both). Default is to fit to both arms.

     *  MISSING.CODE: missing code for genotype calls (default is NA)

     *  keepEmission: return emission probabilities  (not recommended)

     *  keepLikelihod: return likelihood (not recommended)

     *  keepTransitionProb: return transition probabilities (not
        recommended)

     *  SCALE=1: whether to scale the transition probabilities

_V_a_l_u_e:

     An object of the same class

_N_o_t_e:

     further notes

_A_u_t_h_o_r(_s):

_R_e_f_e_r_e_n_c_e_s:

     RB Scharpf et al. (2007), Department of Biostatistics Working
     Papers, Working Paper 136

_S_e_e _A_l_s_o:

     The package 'callsConfidence' is available here: <URL:
     http://www.biostat.jhsph.edu/~rscharpf/software/index.html>

_E_x_a_m_p_l_e_s:

     data(chromosome1)

     ## Not run: 
       callsIce(hmmset) <- FALSE
       copyNumberIce(hmmset) <- FALSE
       fitVanilla <- hmm(hmmset)
       require(callsConfidence)
       callsIce(hmmset) <- TRUE
       copyNumberIce(hmmset) <- TRUE
       fitIce <- hmm(hmmset, flavor="ICE", arm="both")
     ## End(Not run)

