pk2bmkr               package:PROcess               R Documentation

_F_i_n_d _B_i_o_m_a_r_k_e_r_s.

_D_e_s_c_r_i_p_t_i_o_n:

     Align peaks of spectra in `peakinfofile' and find biomarkers by a
     procedure described in Gentleman and Geyer (1994).

_U_s_a_g_e:

     pk2bmkr(peakinfofile, bseoffM, bmkfile, eps = 0.003, binary = F,p.fltr = 0.1)

_A_r_g_u_m_e_n_t_s:

peakinfofile: a `.csv' file in the same format as    Ciphergen's
          peakinfo file with 5 columns  data,  Spectrum.Tag, Spectrum.,
          Peak., Intensity and   Substance.Mass.

 bseoffM: a matrix holding the baseline-substracted  spectra, with
          row-names as the m/z values and  column-names  as the
          spectrum names. 

 bmkfile: a `.csv' file in the same format as    Ciphergen's biomarker
          file, with spectra (samples)  as columns, and biomarkers as
          rows.

     eps: expected experimental variation in the m/z values.

  binary: output intensity or binary peak  presence/absence signals. 

  p.fltr: a number between 0 and 1. If a proto-biomarker  is identified
          as peak in > p.fltr x 100 percent of spectra,  it's kept in
          'bmkfile'. 

_V_a_l_u_e:

     A dataframe with spectra as rows and biomarkers as  columns.
     Spectrum labels and biomarker positions may be in  the names of
     the dataframe.

_A_u_t_h_o_r(_s):

     Xiaochun Li

_R_e_f_e_r_e_n_c_e_s:

     Gentleman, R. and Geyer, C.J. (1994). Maximum  likelihood for
     interval censored data: Consistency and  computation. Biometrika,
     81:618-623.

_S_e_e _A_l_s_o:

     'rmBaseline','getPeaks'

_E_x_a_m_p_l_e_s:

     example(getPeaks)
     bmkfile <- paste(tempdir(),"testbiomarker.csv",sep="/")
     testBio <- pk2bmkr(peakfile, rtM, bmkfile)

     ## plot biomarker intensities of the 2 spectra

     mzs <- as.numeric(rownames(rtM))
     matplot(mzs, rtM, type="l", xlim=c(1000, 10000))

     bks <- getMzs(testBio)
     abline(v=bks, col="green")

