generateExprVal.method.avgdiff     package:affy     R Documentation

_G_e_n_e_r_a_t_e _a_n _e_x_p_r_e_s_s_i_o_n _v_a_l_u_e _f_r_o_m _t_h_e _p_r_o_b_e_s _i_n_f_o_r_m_a_t_i_o_n_s

_D_e_s_c_r_i_p_t_i_o_n:

     Generate an expression from the probes

_U_s_a_g_e:

     generateExprVal.method.avgdiff(probes, ...)
     generateExprVal.method.medianpolish(probes, ...)
     generateExprVal.method.liwong(probes, ...)
     generateExprVal.method.mas(probes, ...)

_A_r_g_u_m_e_n_t_s:

  probes: a matrix of probe intesities with rows representing probes
          and columns representing samples. Usually 'pm(probeset)'
          where 'probeset' is a of class 'ProbeSet'

     ...: extra arguments to pass to the respective function

_V_a_l_u_e:

     A list containing entries: 

   exprs: The expression values.

se.exprs: The standard error estimate.

_S_e_e _A_l_s_o:

     'generateExprSet-methods,\code{generateExprVal.method.playerout},
     \code{li.wong}, \code{medianpolish}'

_E_x_a_m_p_l_e_s:

       data(SpikeIn) ##SpikeIn is a ProbeSets
       probes <- pm(SpikeIn) 
       avgdiff <- generateExprVal.method.avgdiff(probes)
       medianpolish <- generateExprVal.method.medianpolish(probes)
       liwong <- generateExprVal.method.liwong(probes)
       playerout <- generateExprVal.method.playerout(probes)
       mas <- generateExprVal.method.mas(probes)
       
       concentrations <- as.numeric(sampleNames(SpikeIn))
       plot(concentrations,avgdiff$exprs,log="xy",ylim=c(50,10000),pch="a",type="b")
       points(concentrations,2^medianpolish$exprs,pch="m",col=2,type="b",lty=2)
       points(concentrations,liwong$exprs,pch="l",col=3,type="b",lty=3)
       points(concentrations,playerout$exprs,pch="p",col=4,type="b",lty=4)
       points(concentrations,mas$exprs,pch="p",col=4,type="b",lty=4)

       

