Nothing
setClass("mirnapath",
representation(
mirnaTable="data.frame",
columns="character",
groupcount="numeric",
state="character",
mirnaGene="data.frame",
mirnaPathways="data.frame",
pathwaycount="numeric",
filters="numeric",
enrichment="list",
pathwayList="character"),
prototype(
mirnaTable=data.frame(),
columns=character(0),
groupcount=numeric(0),
state=character(0),
mirnaGene=data.frame(),
mirnaPathways=data.frame(),
pathwaycount=numeric(0),
filters=numeric(0),
enrichment=list(),
pathwayList=character(0)),
sealed=TRUE,
package="miRNApath" )
`loadmirnapath` <-
function
( mirnafile = "mirna_input.txt",
mirnacol = "miRNA Name",
assayidcol = "ASSAYID",
groupcol = "GROUP",
filterflagcol = "FILTERFLAG",
expressioncol = NA,
foldchangecol = NA,
pvaluecol = NA)
{
mirnaTable <- read.table(mirnafile, header=TRUE, sep="\t", fill=FALSE, comment.char = "", check.names = FALSE, quote="\"");
# Check columns, that they exist as specified
checkColumns(data = mirnaTable, mandatory = c( mirnacol, groupcol ), numeric = NA );
columns = c( "mirnacol" = mirnacol, "assayidcol" = assayidcol, "groupcol" = groupcol, "filterflagcol" = filterflagcol );
if (!is.na(groupcol))
{
# Count the number of groups in the dataset
groupcount = length(levels(as.factor(mirnaTable[,groupcol])));
} else {
groupcount = 0;
}
# check whether the data is already prepared for enrichment with hits and full library
if ( any( colnames(mirnaTable) %in% filterflagcol ) )
{
state = "filtered";
} else {
state = "unfiltered";
}
#mirnaobj <- list(mirnaTable = mirnaTable, columns = columns, groupcount = groupcount, state = state );
mirnaobj <- new("mirnapath", mirnaTable = mirnaTable, columns = columns, groupcount = groupcount, state = state );
#class(mirnaobj) = "mirnapath";
return(mirnaobj);
}
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