R/MAD.R

In DanteR: Proteomics data analysis tool

# Written by Ashoka D. Polpitiya
# for the Department of Energy (PNNL, Richland, WA)
# Copyright 2007, Battelle Memorial Institute
# E-mail: ashoka.polpitiya@pnl.gov
# Website: http://omics.pnl.gov/software
# -------------------------------------------------------------------------
#
# Licensed under the Apache License, Version 2.0; you may not use this file except
# in compliance with the License.  You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
######################### Global intensity normalization #####

########################### MAD ##################################
# Note: assumes factors table exists
MAD <- function(Data,
                do.factors = FALSE,
                Factor.name = "",
                meanadjust=FALSE)
{
    if (do.factors)
        Data <- MADdata(Data, meanadjust=meanadjust)
    else
    {
#        if(!exists("factors")) stop("Table called 'factors' does not exist")
        factors = get.factors(Data)
        Factor <- factors[,Factor.name]
        Nreps <- unique(as.vector(t(Factor)))
        for (i in 1:length(Nreps)) # for each unique factor level
        {
            idx <- which(Factor == Nreps[i])
            dataset <- Data[,idx] # extract data for factor i
            if (length(idx) > 1) # MAD
            {
                madData <- MADdata(dataset, meanadjust=meanadjust)
                Data[,idx] <- madData
            }
        }
    }
    return(Data)
}

#-----------------------------------------------------------------

MADdata <- function(Data, meanadjust=FALSE)
{
    if (meanadjust)
    {
        colmeans <- colMeans(Data, na.rm=TRUE)
        Data <- Data - colmeans
    }
    colMad <- apply(Data,2,"mad",na.rm=TRUE)
    GMmad <- exp(mean(log(colMad),na.rm=TRUE)) # geometric mean

    for (i in 1:dim(Data)[2])
    {
        Data[,i] <- Data[,i] / (mad(Data[,i],na.rm=TRUE)/GMmad)
    }
    if (meanadjust)
        return(Data + colmeans)
    else
        return(Data)
}