loadmirnapath: Load miRNApath Data
In miRNApath: miRNApath: Pathway Enrichment for miRNA Expression Data

Description Usage Arguments Details Value Author(s) References See Also Examples

This method loads data from a tab-delimited flatfile into an object of type mirnapath to be used for further miRNA analysis.

loadmirnapath(mirnafile="mirna_input.txt", mirnacol="miRNA Name",
    assayidcol="ASSAYID", groupcol="GROUP", 
    filterflagcol="FILTERFLAG", expressioncol=NA, 
    foldchangecol=NA, pvaluecol=NA)

`mirnafile`	The tab-delimited miRNA results file to be loaded. The file is expected to be in tall-skinny format.
`mirnacol`	The name of the column header which contains the miRNA names being assayed.
`assayidcol`	The name of the column containing values which distinguish different assays for the same miRNA.
`groupcol`	The (optional) name of the column which contains sample group information. Enrichment is run separately for each sample group, defining a unique universe for the basis of the enrichment.
`filterflagcol`	The column header which does or will contain a flag distinguishing hits from non-hits. This column is typically not supplied and is created during the `filtermirnapath` step.
`expressioncol`	The (optional) column header for values containing the expression abundances of the miRNAs assayed.
`foldchangecol`	The (optional) column header for values containing the fold changes of the miRNAs assayed.
`pvaluecol`	The (pvaluecol) column header for values containing the P-values of the miRNAs assayed.

This method is the primary means for loading data into the miRNApath package.

Data is not assumed to have any particular numerical values, however the basic column types are typically used: expression abundance, fold change, and P-value. Should one or more columns be specified and available, it will be available for filtering later on with filtermirnapath.

The group column assumes there is one column containing all sample group information.

The assayid column is used to distinguish multiple assays for the same miRNA, such as different vendors, or even different preparations of the same miRNA assay.

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.

James M. Ward jmw86069@gmail.com

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.

loadmirnapath, filtermirnapath, loadmirnatogene, loadmirnapathways

## Start with miRNA data from this package
data(mirnaobj);

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

## Now essentially load it back, but assign column headers
mirnaobj <- loadmirnapath( mirnafile = "mirnaobj.txt",
    pvaluecol = "P-value", groupcol = "GROUP", 
    mirnacol = "miRNA Name", assayidcol = "ASSAYID" );

## Display summary information for the resulting object
mirnaobj;