FluidigmDataConversion: Correct orientation of data for model analysis.

In bvnlab/SCATTome: FluidgmR

Description

Corrects data organization for model analysis. The genes are transferred along columns and samples are transferred along rows for further analysis.

Usage

FluidigmDataConversion(d, Cell = 2, Gene = 5, Value = 7)

Arguments

d
Cell
Gene
Value

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (d, Cell = 2, Gene = 5, Value = 7) 
{
    d1 <- as.data.frame(d[, c(Cell, Gene, Value)])
    for (i in 1:length(d1[, 3])) {
        if (d1[i, 3] == 999) 
            d1[i, 3] = NA
    }
    colnames(d1) <- c("c", "g", "v")
    CellNames <- na.omit(unique(d1[, 1]))
    GeneNames <- na.omit(unique(d1[, 2]))
    dat <- as.data.frame(matrix(nrow = length(CellNames), ncol = length(GeneNames)))
    colnames(dat) <- GeneNames
    rownames(dat) <- CellNames
    for (i in 1:length(CellNames)) {
        for (j in 1:length(GeneNames)) {
            dat[i, j] <- d1[which((as.character(d1$c) == as.character(CellNames[i])) & 
                (as.character(d1$g) == as.character(GeneNames[j]))), 
                3]
        }
    }
    dat <- cbind(CellNames, dat)
    colnames(dat) <- c("CellNames", GeneNames)
    write.csv(dat, "FluidigmDataConverted.csv", quote = FALSE, 
        row.names = FALSE)
    return(NULL)
  }

bvnlab/SCATTome documentation built on May 13, 2019, 9:05 a.m.