callEmission           package:VanillaICE           R Documentation

_C_a_l_c_u_l_a_t_e _e_m_i_s_s_i_o_n _p_r_o_b_a_b_i_l_i_t_i_e_s _f_o_r _t_h_e _I_C_E _H_M_M

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

     When confidence estimates are incorporated in the ICE HMM for
     genotype calls, the observed data at a SNP is the genotype call
     and the uncertainty measure. The joint distribution of the call
     and the uncertainty measure depends on the underlying hidden
     state.  This function calculates the emission probability for the
     joint sequence of calls and confidence scores. See reference for
     additioal details.

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

     callEmission(object, P.CHOM.Normal, P.CHOM.LOH, SAMPLE=1)

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

  object: An object inheriting from 'AnnotatedSnpSet'

P.CHOM.Normal: probability of called homozygous given the true
          underlying state is normal (retention of heterozygosity)

P.CHOM.LOH: probability of called homozygous given the true underlying
          state is loss of heterozygosity

  SAMPLE: Integer: which sample

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

     This function is essentially a wrapper for
     'getHapmapProbabilities' that allows the object to contain the
     merged 50k Xba and Hind chips, or the merged 250k Nsp and Sty
     chips. Because the distribution of the uncertainty estimates are
     chip-specific (enzyme-specific), this function computes
     enzyme-specific emission probabilities (note: one of the columns
     in 'featureData' must have the name 'enzyme' and the elements in
     the vector must be 'Xba' and 'Hind' or 'Nsp' and 'Sty'.).

     The annotation slot in the object must contain one of the
     following strings that identifies the Affymetrix chip:

     mapping100k (if the 50k xba and 50k hind results have been merged
     into one object)

     pd.mapping50k.xba240  (50k Xba platform)

     pd.mapping50k.hind240 (50k Hind)

     mapping500k  (if the two 250k chips - Nsp and Sty - have been
     merged)

     pd.mapping250k.nsp

     pd.mapping250k.sty

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

_N_o_t_e:

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

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

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

     'getHapmapProbabilities',   'crlmm', 'featureData' For the
     callsConfidence package, see <URL:
     http://www.biostat.jhsph.edu/~rscharpf/software/index.html>

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

       data(chromosome1)
       ##Create an object of class AnnotatedSnpCallSet
       callset <- new("AnnotatedSnpSet",
                      calls=calls(chromosome1),
                      callsConfidence=callsConfidence(chromosome1),
                      featureData=featureData(chromosome1),
                      phenoData=phenoData(chromosome1),
                      annotation=annotation(chromosome1))
       ##1 = homozygous (AA or BB), 2 = heterozygous
       calls(callset)[calls(callset) == 3] <-  1
       ##make sure that enzyme information is stored in featureData

     ## Not run: 
       require("callsConfidence")
         emissionProb <- callEmission(object=callset,
                                      P.CHOM.Normal=0.70,
                                      P.CHOM.LOH=0.999)
         range(emissionProb)
     ## End(Not run)

