peaksAlignment-class         package:flagme         R Documentation

_D_a_t_a _S_t_r_u_c_t_u_r_e _f_o_r _p_a_i_r_w_i_s_e _a_l_i_g_n_m_e_n_t _o_f _2 _G_C_M_S _s_a_m_p_l_e_s

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

     Store the raw data and optionally, information regarding signal
     peaks for a number of GCMS runs

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

     peaksAlignment(d1,d2,t1,t2,gap=.5,D=1000,timedf=NULL,df=30,verbose=TRUE,usePeaks=TRUE,compress=TRUE)

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

      d1: matrix of MS intensities for 1st sample (if doing a peak
          alignment, this contains peak apexes/areas; if doing a
          profile alignment, this contains scan intensities.  Rows are
          m/z bins, columns are peaks/scans.

      d2: matrix of MS intensities for 2nd sample

      t1: vector of retention times for 1st sample

      t2: vector of retention times for 2nd sample

     gap: gap penalty for dynamic programming algorithm

       D: time penalty (on same scale as retention time differences,
          't1' and 't2')

  timedf: list (length = the number of pairwise alignments) of matrices
          giving the expected time differences expected at each pair of
          peaks (used with 'usePeaks'='TRUE'.

      df: integer, how far from the diagonal to go to calculate the
          similarity of peaks.  Smaller value should run faster, but be
          careful not to choose too low.

 verbose: logical, whether to print out info.

usePeaks: logical, 'TRUE' uses 'peakdata' list, 'FALSE' uses 'rawdata'
          list for computing similarity.

compress: logical, whether to compress the similarity matrix into a
          sparse format.

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

     peaksAlignment is a hold-all data structure of the raw and peak
     detection data.

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

     'peaksAlignment' object

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

     Mark Robinson

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

     Mark D Robinson (2008).  Methods for the analysis of gas
     chromatography - mass spectrometry data _PhD dissertation_
     University of Melbourne.

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

     'peaksDataset', 'clusterAlignment'

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

     # see clusterAlignment, it calls peaksAlignment

