multipleAlignment-class        package:flagme        R Documentation

_D_a_t_a _S_t_r_u_c_t_u_r_e _f_o_r _m_u_l_t_i_p_l_e _a_l_i_g_n_m_e_n_t _o_f _m_a_n_y _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:

     multipleAlignment(pd,group,bw.gap=0.8,wn.gap=0.6,bw.D=.20,wn.D=.05,filterMin=3,lite=FALSE,usePeaks=TRUE,df=50,verbose=TRUE,timeAdjust=FALSE,doImpute=FALSE)

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

      pd: a 'peaksDataset' object

   group: factor variable of experiment groups, used to guide the
          alignment algorithm

  bw.gap: gap parameter for "between" alignments

  wn.gap: gap parameter for "within" alignments

    bw.D: distance penalty for "between" alignments

    wn.D: distance penalty for "within" alignments

filterMin: minimum number of peaks within a merged peak to be kept in
          the analysis

    lite: logical, whether to keep "between" alignment details
          (default, 'FALSE')

usePeaks: logical, whether to use peaks (if 'TRUE') or the full 2D
          profile alignment (if 'FALSE')

      df: distance from diagonal to calculate similarity

 verbose: logical, whether to print information

timeAdjust: logical, whether to use the full 2D profile data to
          estimate retention time drifts (Note: time required)

doImpute: logical, whether to impute the location of unmatched peaks

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

     multipleAlignment is the data structure giving the result of an
     alignment across several GCMS runs.

     Multiple alignments are done progressively.  First, all samples
     with the same 'tg$Group' label with be aligned (denoted a "within"
     alignment).  Second, each group will be summarized into a
     pseudo-data set, essentially a spectrum and retention time for
     each matched peak of the within-alignment.  Third, these "merged
     peaks" are aligned in the same progressive manner, here called a
     "between" alignment.

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

     'multipleAlignment' 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', 'betweenAlignment', 'progressiveAlignment'

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

     require(gcspikelite)

     # paths and files
     gcmsPath<-paste(.find.package("gcspikelite"),"data",sep="/")
     cdfFiles<-dir(gcmsPath,"CDF",full=TRUE)
     eluFiles<-dir(gcmsPath,"ELU",full=TRUE)

     # read data, peak detection results
     pd<-peaksDataset(cdfFiles[1:2],mz=seq(50,550),rtrange=c(7.5,8.5))
     pd<-addAMDISPeaks(pd,eluFiles[1:2])

     # multiple alignment
     ma<-multipleAlignment(pd,c(1,1),wn.gap=0.5,wn.D=.05,bw.gap=0.6,bw.D=.2,usePeaks=TRUE,filterMin=1,df=50,verbose=TRUE)

