addMethod {SummarizedBenchmark} | R Documentation

## Add new method to BenchDesign object

### Description

This function takes a BenchDesign object and returns a modified object with the specified method included. At a minimum, a string name for the method, `label`, and the workhorse function for the method, `func`, must be specified in addition to the primary BenchDesign object.

### Usage

    addMethod(bd, label, func, params = rlang::quos(), post = NULL,
      meta = NULL)

### Arguments

`bd` | BenchDesign object.
`label` | Character name for the method.
`func` | Primary function to be benchmarked.
`params` | Named quosure list created using `rlang::quos` of `parameter = value` pairs to be passed to `func`.
`post` | Optional post-processing function that takes results of `func` as input. Ignored if NULL. If multiple assays (metrics) should be generated for each method, this can be accomplished by specifying a named list of post-processing functions, one for each assay. (default = NULL)
`meta` | Optional metadata information for method to be included in `colData` of `SummarizedBenchmark` object generated using `buildBench`. See Details for more information. Ignored if NULL. (default = NULL)

### Details

The inputs for the call to `label` should be specified as `parameter = value` pairs, where the `value` can be any fixed value, variable, or column in the `bdata` of the BenchDesign object.

An optional secondary function, `post`, can be specified if the output of the workhorse function, `func`, needs to be further processed. As an example, `post` may be a simple "getter" function for accessing the column of interest from the large object returned by `func`.

The optional `meta` parameter accepts a named list of metadata tags to be included for the method in the resulting `SummarizedBenchmark` object. This can be useful for two primary cases. First, it can help keep analyses better organized by allowing the specification of additional information that should be stored with methods, e.g. a tag for "method type" or descriptive information on why the method was included in the comparison. Second, and more improtantly, the `meta` parameter can be used to overwrite the package and version information that is automatically extracted from the function specified to `func`. This is particularly useful when the function passed to `func` is a wrapper for a script in (or outside of) R, and the appropriate package and version information can't be directly pulled from `func`. In this case, the user can either manually specify the `"pkg_name"` and `"pkg_vers"` values to `meta` as a list, or specify a separate function that should be used to determine the package name and version. If a separate function should be used, it should be passed to `meta` as a list entry with the name `pkg_func` and first quoted using `rlang::quo`, e.g. `list(pkg_func = quo(p.adjust))`.

### Value

A copy of the originally supplied BenchDesign with the new method added.

### Author(s)

Patrick Kimes

### Examples

    ## create example data set of p-values
    df <- data.frame(pval = runif(100))

    ## example calculating qvalue from pvalues

    ## using standard call
    qv <- qvalue::qvalue(p = df$pval)
    qv <- qv$qvalue

    ## adding same method to BenchDesign
    bench <- BenchDesign(data = df)
    bench <- addMethod(bench,
                       label = "qv",
                        func = qvalue::qvalue,
                        post = function(x) { x$qvalue },
                        params = rlang::quos(p = pval))

[Package SummarizedBenchmark version 2.0.1 Index]