KCsmart-package           package:KCsmart           R Documentation

_K_C_s_m_a_r_t

_D_e_s_c_r_i_p_t_i_o_n:

     Multiple sample aCGH analysis using kernel convolution

_D_e_t_a_i_l_s:


       Package:  KCsmart
       Type:     Package
       Version:  1.0
       Date:     2008-08-14
       License:  GPL

     Use the wrapper function 'calcSpm' to calculate the sample point
     matrix. Use 'findSigLevelTrad' to find a significance threshold
     using permutation based testing. Use 'plot' to plot the sample
     point matrix or 'plotScaleSpace' to plot the significant regions
     over multiple scales (sigmas). Use 'getSigSegments' to retrieve
     the significantly gained and lost regions using specific cutoffs.

_A_u_t_h_o_r(_s):

     Jorma de Ronde, Christiaan Klijn

     Maintainer: Jorma de Ronde <j.d.ronde@nki.nl>

_R_e_f_e_r_e_n_c_e_s:

     Identification of cancer genes using a statistical framework for
     multiexperiment analysis of nondiscretized array CGH data. Nucleic
     Acids Res. 2008 Feb;36(2):e13.

_S_e_e _A_l_s_o:

     'calcSpm',  'findSigLevelTrad', 'findSigLevelFdr', 'plot',
     'plotScaleSpace', 'getSigSegments'

_E_x_a_m_p_l_e_s:

     data(hsSampleData)
     data(hsMirrorLocs)

     spm1mb <- calcSpm(hsSampleData, hsMirrorLocs)
     spm4mb <- calcSpm(hsSampleData, hsMirrorLocs, sigma=4000000)

     plot(spm1mb)
     plot(spm1mb, chromosomes=c(1,5,6,'X'))

     siglevel1mb <- findSigLevelTrad(hsSampleData, spm1mb, n=3)
     siglevel4mb <- findSigLevelTrad(hsSampleData, spm4mb, n=3)

     plot(spm1mb, sig.level=siglevel1mb)

     plotScaleSpace(list(spm1mb, spm4mb), list(siglevel1mb, siglevel4mb), type='g')

     sigSegments1mb <- getSigSegments(spm1mb, siglevel1mb)

