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.
Details
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.
Value
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.
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.
## 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;
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(miRNApath)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/miRNApath/loadmirnapath.Rd_%03d_medium.png", width=480, height=480)
> ### Name: loadmirnapath
> ### Title: Load miRNApath Data
> ### Aliases: loadmirnapath
> ### Keywords: IO manip
>
> ### ** Examples
>
>
> ## 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;
mirnapath object:
Length Class Mode
1 mirnapath S4
Columns specified:
mirnacol = "miRNA Name"
assayidcol = "ASSAYID"
groupcol = "GROUP"
filterflagcol = "FILTERFLAG"
Filters Applied:
none
Number of miRNAs: 196
Number of sample groups: 18
Number of pathways: NA
State: filtered
>
>
>
>
>
> dev.off()
null device
1
>