"FCSmetadata-class"         package:rflowcyt         R Documentation

_C_l_a_s_s "_F_C_S_m_e_t_a_d_a_t_a" _M_e_t_a_d_a_t_a _p_o_r_t_i_o_n _o_f _a _F_l_o_w _C_y_t_o_m_e_t_r_y _S_t_a_n_d_a_r_d
_o_b_j_e_c_t

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

     Information from the HEADER and TEXT of a raw binary FCS file
     about the data and other parameters are stored in the metadata.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created by calls of the form 'new("FCSmetadata",
     ...)'.

_S_l_o_t_s:

     '_m_o_d_e': Object of class '"character"' the "$MODE" mode of the raw
          binary FCS file

     '_s_i_z_e': Object of class '"numeric"' the "$TOT" row dimension of
          the data; describing the number of observations or cells 

     '_n_p_a_r_a_m': Object of class '"numeric"' the "$PAR" column dimension
          of the data; describing the number of parameters 

     '_s_h_o_r_t_n_a_m_e_s': Object of class '"vector"' the "$PnN" short names
          corresponding to the column variables of the data; these
          names are generally non-descript and are not used as the
          names of the columns of the data

     '_l_o_n_g_n_a_m_e_s': Object of class '"vector"' the "$PnS" long names used
          for the column variables of the data

     '_p_a_r_a_m_r_a_n_g_e_s': Object of class '"vector"' the "$PnR" maximum value
          corresponding to the column variables

     '_f_i_l_e_n_a_m_e': Object of class '"character"' path and/or name of the
          *original* raw binary FCS object  

     '_o_b_j_e_c_t_n_a_m_e': Object of class '"character"' the name of the
          original, 'FCS-class' object

     '_o_r_i_g_i_n_a_l': Object of class '"logical"' the original status of the
          current object 

     '_f_c_s_i_n_f_o': Object of class '"list"' the other parameters and
          values in the HEADER and TEXT of the raw binary FCS file 

_M_e_t_h_o_d_s:

     "[" 'signature(x = "FCSmetadata")': Extracts the metadata slots or
          metadata@fcsinfo slots by using a single character name
          index; Extracts the metadata@fcsinfo slots by using a single
          or vector of numerical indicies  

     "[<-" 'signature(x = "FCSmetadata")': Replaces the metadata slots
          or metadata@fcsinfo slots by using a single character name
          index; Replaces the metadata@fcsinfo slots by using a single
          or vector of numerical indicies;Adds a new slot to the
          metadata@fcsinfo 

     "[[" 'signature(x = "FCSmetadata")':  Extracts the metadata slots
          or metadata@fcsinfo slots by using a single character name
          index; Extracts the metadata@fcsinfo slots by using a single
          or vector of numerical indicies 

     "[[<-" 'signature(x = "FCSmetadata")': Replaces the metadata slots
          or metadata@fcsinfo slots by using a single character name
          index; Replaces the metadata@fcsinfo slots by using a single
          or vector of numerical indicies;Adds a new slot to the
          metadata@fcsinfo

     "_p_r_i_n_t-_m_e_t_h_o_d_s" 'signature(x = "FCSmetadata")': prints the
          original status, the objectname, filename, and dimensions of
          the data

     "_s_h_o_w-_m_e_t_h_o_d_s" 'signature(object = "FCSmetadata")': same as
          'print' 

     "_s_u_m_m_a_r_y-_m_e_t_h_o_d_s" 'signature(object = "FCSmetadata")': summaries
          the metadata in a string output 

_N_o_t_e:

     For more information about the different parameters in the
     metadata@fcsinfo slot, please look at the documentation for
     'read.FCS'.

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

     A.J. Rossini, J.Y. Wan, and Zoe Moodie

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

     Trevor Hastie, Robert Tibshirani, and Jerome Friedman. The
     Elements of Statistical Learning: Data Mining, Inference, and
     Prediction. Springer Series in Statistics : New York, 2001.
     pp.279-283.

     Jerome H. Friedman and Nicholas I. Fisher. Bump Hunting in
     High-Dimensional Data. Tech Report. October 28, 1998.

     J. Paul Robinson, et al. Current Protocols in Cytometry.  John
     Wiley & Sons, Inc : 2001.

     Mario Roederer and Richard R. Hardy. Frequency Difference Gating:
     A Multivariate Method for Identifying Subsets that Differe between
     Samples. Cytometry, 45:56-64, 2001.

     Mario Roederer and Adam Treister and Wayne Moore and Leonore A.
     Herzenberg. Probability Binning Comparison: A Metric for
     Quantitating Univariate Distribution Differences. Cytometry,
     45:37-46, 2001.

     Keith A. Baggerly. Probability Binning and Testing Agreement
     between Multivariate Immunofluorescence Histograms: Extending the
     Chi-Squared Test. Cytometry, 45:141-150, 2001.

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

     'read.FCS',  '"FCS-class"', '"print-methods"', '"show-methods"',
     '"summary-methods"', '"subset-methods"', '"subset2-methods"',
     '"subsetassign-methods"', '"subset2assign-methods"'

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

     default<-new("FCSmetadata")

     some.meta<-new("FCSmetadata", fcsinfo=list("comment"=rep("none", 10)),
     mode="none", nparam=0, size=0)

     ## extract/subset the metadata
     some.meta[["nparam"]]
     some.meta["paramranges"]
     ## replace the metadata/subsetassign the metadata
     ## 3 parameters with ranges
     some.meta[["nparam"]]<-3
     some.meta["paramranges"]<-rep(1,3)
     ## show
     show(some.meta)
     ## print
     print(some.meta)
     some.meta
     ## summary
     summary(some.meta)

