Takes a BenchDesign object and the definition of a new method for benchmarking and returns the original BenchDesign with the new method included.

At a minimum, a method label (label =), and the workhorse function for the method (func =) must be specified for the new method.

Parameters for the method must be specified as a quos named list of parameter = value pairs mapping entries in the benchmarking data to the function parameters. For users familiar with the ggplot2 package, this can be viewed similar to the aes = mapping of data to geometry parameters.

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.

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



BenchDesign object.


Character name for the method.


Primary function to be benchmarked.


Named quosure list created using quos of parameter = value pairs to be passed to func.


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)


Optional metadata information for method to be included in colData of SummarizedBenchmark object generated using link{buildBench}. See Details for more information. Ignored if NULL. (default = NULL)


Modified BenchDesign object with new method added.


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 quo, e.g. list(pkg_func = quo(p.adjust)).

See also


## 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))