03.ReadingData             package:limma             R Documentation

_R_e_a_d_i_n_g _M_i_c_r_o_a_r_r_a_y _D_a_t_a _f_r_o_m _F_i_l_e_s

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

     This help page gives an overview of LIMMA functions used to read
     data from files.

_R_e_a_d_i_n_g _T_a_r_g_e_t _I_n_f_o_r_m_a_t_i_o_n:

     The function 'readTargets' is designed to help with organizing
     information about which RNA sample is hybridized to each channel
     on each array and which files store information for each array.

_R_e_a_d_i_n_g _I_n_t_e_n_s_i_t_y _D_a_t_a:

     The first step in a microarray data analysis is to read into R the
     intensity data for each array provided by an image analysis
     program. This is done using the function 'read.maimages'.

     'read.maimages' optionally constructs quality weights for each
     spot using quality functions listed in QualityWeights.

     'read.maimages' produces an 'RGList' object and stores only the
     information required from each image analysis output file. If you
     wish to read all the image analysis output files into R as
     individual data frames preserving all the original columns found
     in the files, you may use 'read.series'. An 'RGList' object can be
     extracted from the data frames at a later stage using the
     functions 'rg.spot', 'rg.genepix' or 'rg.quantarray'.

     Another function, 'rg.series.spot' is very similar to
     'read.maimages' with 'source="spot"'. This function will be
     removed in future versions of LIMMA.

     'read.maimages' uses utility functions 'removeExt', 'read.matrix',
     'read.imagene' and 'read.columns'. There are also a series of
     utility functions which read the header information from image
     output files including 'readGPRHeader', 'readImaGeneHeader' and
     'readGenericHeader'.

     The function as.MAList can be used to convert a 'marrayNorm'
     object to an 'MAList' object if the data was read and normalized
     using the marray and marrayNorm packages.

_R_e_a_d_i_n_g _t_h_e _G_e_n_e _L_i_s_t:

     Most image analysis software programs provide gene IDs as part of
     the intensity output files, for example GenePix, Imagene and the
     Stanford Microarray Database do this. In other cases the probe ID
     and annotation information may be in a separate file. The most
     common format for the probe annotation file is the GenePix Array
     List (GAL) file format. The function 'readGAL' reads information
     from a GAL file and produces a data frame with standard column
     names.

     The function 'getLayout' extracts from the GAL-file data frame the
     print layout information for a spotted array. The functions
     'gridr', 'gridc', 'spotr' and 'spotc' use the extracted layout to
     compute grid positions and spot positions within each grid for
     each spot. The function 'printorder' calculates the printorder,
     plate number and plate row and column position for each spot given
     information about the printing process. The utility function
     'getSpacing' converts character strings specifying spacings of
     duplicate spots to numeric values.

     The Australian Genome Research Facility in Australia often
     produces GAL files with composite probe IDs or names consisting of
     multiple strings separated by a delimiter. These can be separated
     into name and annotation information using 'strsplit2'.

     If each probe is printed more than once of the arrays in a regular
     pattern, then 'uniquegenelist' will remove duplicate names from
     the gal-file or gene list.

_I_d_e_n_t_i_f_y_i_n_g _C_o_n_t_r_o_l _S_p_o_t_s:

     The functions 'readSpotTypes' and 'controlStatus' assist with
     separating control spots from ordinary genes in the analysis and
     data exploration.

_M_a_n_i_p_u_l_a_t_i_n_g _D_a_t_a _O_b_j_e_c_t_s:

     'cbind', 'rbind', 'merge' allow different 'RGList' or 'MAList'
     objects to be combined. 'cbind' combines data from different
     arrays assuming the layout of the arrays to be the same. 'merge'
     can combine data even when the order of the probes on the arrays
     has changed. 'merge' uses utility function 'makeUnique'.

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

     Gordon Smyth

