compute.sliding            package:macat            R Documentation

_C_o_m_p_u_t_e _a_n_d _p_l_o_t _s_m_o_o_t_h_i_n_g _o_f _e_x_p_r_e_s_s_i_o_n _v_a_l_u_e_s _o_r _s_c_o_r_e_s _a_l_o_n_g _t_h_e _c_h_r_o_m_o_s_o_m_e

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

     'compute.sliding' computes a smoothing of the expression data or
     scores along the chromosome using the specified kernel function.
     This function is also used within the 'evalScoring' function.
     'plotSliding' creates a plot of the smoothed expression values /
     scores.

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

     compute.sliding(data, chromosome, sample, kernel, kernelparams=NULL, step.width = 1e+06)
     plotSliding(data, chromosome, sample, kernel, kernelparams=NULL,
     step.width=1000000, ...)

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

    data: A MACATData list holding the Expression values and gene
          locations

chromosome: the chromosome to be smoothed

  sample: the sample (patient) whose expression values are smoothed 

  kernel: a kernel function (one of rbf, kNN, basePairDistance or your
          own) 

kernelparams: a list of named parameters for the kernel (by default
          estimated from the data) 

step.width: the smoothing is computed stepwise every step.width
          basepairs  (default is 100000) 

     ...: further graphical parameters passed on to 'plot.default'

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

     for 'compute.sliding': a matrix of dimension (steps x 2) with in
     the first column the locations in basepairs where an interpolation
     is computed, and in the second column the smoothed values.
     'plotSliding' does not return anything and is merely called for
     its side-effect producing the plot.

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

     MACAT development team

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

     'kernelize', 'evalScoring'

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

     data(stjd)
     # just compute smoothed values:
     smooth = compute.sliding(stjd, chromosome=3, sample=6, rbf,
                              kernelparams=list(gamma=1/10^13))
     # compute and plot smoothed values:
     plotSliding(stjd, chromosome=3, sample=6,rbf,
                 kernelparams=list(gamma=1/10^13),pch=20,
                 main="Chromosome 3")

