loadmirnatogene          package:miRNApath          R Documentation

_L_o_a_d _m_i_R_N_A _t_o _g_e_n_e _a_s_s_o_c_i_a_t_i_o_n_s _f_o_r _m_i_R_N_A_p_a_t_h

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

     This method loads associations between miRNAs to the genes they
     affect.

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

     loadmirnatogene(mirnafile, mirnaobj, mirnacol="miRNA Name",
     genecol="Entrez Gene ID", columns=NA)

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

mirnafile: The tab-delimited miRNA results file to be loaded. The file
          is expected to be in tall-skinny format. 

mirnaobj: An object of type mirnapath containing data resulting from
          the 'loadmirnapath' method. 

mirnacol: The name of the column header which contains the miRNA names
          being assayed. That is, the name of the column header in the
          file being read. 

 genecol: The name of the column header which contains the gene names
          being assayed. 

 columns: The names of any additional columns in the file being read
          which should equate with the mirnapath object. 

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

     The data is expected to have miRNA names which exactly match those
     in the mirnaTable item of the mirnapath object. Also, the gene
     names are expected to match exactly with those gene names loaded
     by 'loadmirnapathways'.

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

     The method returns an object of type mirnapath, a list with
     components:

 mirnaTable : data.frame containing the miRNA results data 

 columns : list containing the names of required column headers
          associated to the actual column header supplied in the
          dataset contained in mirnaTable. Required headers: mirnacol,
          assayidcol. Optional headers: groupcol, pvaluecol,
          foldchangecol, expressioncol, filterflagcol 

 groupcount : the number of groups contained in mirnaTable using the
          groupcol, if supplied 

  state : the current state of the object, using the following values
          in order of progress through the typical workflow:
          unfiltered, filtered, enriched. 

_W_a_r_n_i_n_g:

     ....

_N_o_t_e:

     ~~further notes~~ 

     ~Make other sections like Warning with \section{Warning }{....} ~

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

     James M. Ward jmw86069@gmail.com

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

     John Cogswell (2008) Identification of miRNA changes in
     Alzheimer's disease brain and CSF yields putative  biomarkers and
     insights into disease pathways, Journal of Alzheimer's Disease 14,
     27-41.

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

     'loadmirnapath' 'filtermirnapath' 'loadmirnatogene'
     'loadmirnapathways'

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

     ## Load miRNA expression data from AD miRNA paper
     ## This data contains miRNA expression data, 
     data(mirnaobj);

     ## Display the state, which should generally be "unfiltered"
     ## at this point
     mirnaobj@state;

     ## Display summary information about the object
     mirnaobj;

     ## Annotate hits by filtering by P-value 0.05
     mirnaobj <- filtermirnapath( mirnaobj, pvalue = 0.05,
         expression = NA, foldchange = NA );

     ## Write a file as example of required input
     write.table(mirnaobj@mirnaGene, file = "mirnaGene.txt", 
         quote = FALSE, row.names = FALSE, col.names = TRUE, na = "",
         sep = "\t");

     ## Load the miRNA to gene associations
     mirnaobj <- loadmirnatogene( mirnafile = "mirnaGene.txt",
         mirnaobj = mirnaobj, mirnacol = "miRNA Name",
         genecol = "Entrez Gene ID", 
         columns = c(assayidcol = "ASSAYID") );

     ## Display summary, noting the number of genes reported
     mirnaobj;

