esApply {Biobase} | R Documentation

## An apply-like function for ExpressionSet and related structures.

### Description

`esApply` is a wrapper to `apply` for use with `ExpressionSet`s. The application of a function to rows of an expression array usually involves variables in `pData`. `esApply` uses a special evaluation paradigm to make this easy. The function `FUN` may reference any data in `pData` by name.

### Usage

    esApply(X, MARGIN, FUN, ...)

### Arguments

`X` | An instance of class `ExpressionSet`.
`MARGIN` | The margin to apply to, either 1 for rows (samples) or 2 for columns (features).
`FUN` | Any function
`...` | Additional parameters for `FUN`.

### Details

The `pData` from `X` is installed in an environment. This environment is installed as the environment of `FUN`. This will then provide bindings for any symbols in `FUN` that are the same as the names of the `pData` of `X`. If `FUN` has an environment already it is retained but placed after the newly created environment. Some variable shadowing could occur under these circumstances.

### Value

The result of `with(pData(x), apply(exprs(X), MARGIN, FUN, ...))`.

### Author(s)

V.J. Carey <stvjc@channing.harvard.edu>, R. Gentleman

### See Also

`apply`, `ExpressionSet`

### Examples

    data(sample.ExpressionSet)
    ## sum columns of exprs
    res <- esApply(sample.ExpressionSet, 1, sum)

    ## t-test, spliting samples by 'sex'
    f <- function(x) {
        xx <- split(x, sex)
        t.test(xx[[1]], xx[[2]])$p.value
    }
    res <- esApply(sample.ExpressionSet, 1, f)

    ## same, but using a variable passed in the function call

    f <- function(x, s) {
        xx <- split(x, s)
        mean(xx[[1]]) - mean(xx[[2]])
    }
    sex <- sample.ExpressionSet[["sex"]]
    res <- esApply(sample.ExpressionSet, 1, f, s = sex)

    # obtain the p-value of the t-test for sex difference
    mytt.demo <- function(y) {
     ys <- split(y, sex)
     t.test(ys[[1]], ys[[2]])$p.value
    }
    sexPValue <- esApply(sample.ExpressionSet, 1, mytt.demo)

    # obtain the p-value of the slope associated with score, adjusting for sex
    # (if we were concerned with sign we could save the z statistic instead at coef[3,3]
    myreg.demo <- function(y) {
       summary(lm(y ~ sex + score))$coef[3,4]
    }
    scorePValue <- esApply(sample.ExpressionSet, 1, myreg.demo)

    # a resampling method
    resamp <- function(ESET) {
     ntiss <- ncol(exprs(ESET))
     newind <- sample(1:ntiss, size = ntiss, replace = TRUE)
     ESET[newind,]
    }

    # a filter
    q3g100filt <- function(eset) {
     apply(exprs(eset), 1, function(x) quantile(x,.75) > 100)
    }

    # filter after resampling and then apply
    set.seed(123)
    rest <- esApply({bool <- q3g100filt(resamp(sample.ExpressionSet)); sample.ExpressionSet[bool,]},
                    1, mytt.demo)

[Package Biobase version 2.50.0 Index]