R/SFnormalize.R

Defines functions SFnormalize

Documented in SFnormalize

SFnormalize <- function(data, flag = 1) {

    n <- ncol(data)
    p <- nrow(data)

    ## identify low expression samples
    if (length(flag) == 1) {
        if (flag == 1) { 
            medcov <- apply(data, 2, function(x) median(x[x > 0]))
            percov <- apply(data, 2, function(x) mean(x > 0))
            flag <- (medcov < 5) | (percov < .1)
        } else if (flag == 0) {
            flag <- as.logical(rep(0, n))
        } else { 
            stop("flag must be 0, 1 or logical n-vector.")
        }

    } else if (length(flag) != n | !is.logical(flag)) {
        stop("flag must be 0, 1 or logical n-vector.")
    }

    if (sum(!flag) < 3) {
        stop("Too many lowly expressed samples to carry out 
             normalization procedure.
             Must have at least 3 samples above threshold.
             More samples are recommended for reasonable 
             inference from p-value.")
    }

    ## normalize non-low expression samples
    data.norm <- data[, !flag]
    coverage <- apply(data.norm, 2, sum)
    data.norm <- apply(data.norm, 2, 
                       function(x) x / sum(x) * median(coverage))

    return(list(data.norm = data.norm,
                flag = flag))
}

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SigFuge documentation built on Nov. 1, 2018, 2:20 a.m.