rankFeatures-MultiAssayExperiment-method: Rank the Features in a 'MultiAssayExperiment' Object
In bhklab/PanCuRx: Pancreatic Ductal Adenocarcinoma Tool-Kit

Description Usage Arguments Value See Also

Rank the Features in a MultiAssayExperiment Object

## S4 method for signature 'MultiAssayExperiment'
rankFeatures(
  object,
  FUN = "mad",
  RANK_FUN = "dense_rank",
  ...,
  descending = TRUE,
  weights
)

`object`	A `MultiAssayExperiment` to rank the features in.
`FUN`	A vectorized feature scoring function, such as `var` or `mad`. Defaults to `mad` from the `BiocGenerics` package.
`RANK_FUN`	A ranking function, such as `rank` or `dense_rank`. Defaults to `dense_rank` from `dplyr`.
`...`	Fall through arguments to `FUN`, such as `na.rm=TRUE`.
`descending`	Should your rank function be called with `-` before the values from `FUN`. Defaults to `TRUE`, which should be used if high values returned from `FUN` are good.
`weights`	A named `numeric` weighting vector with a weight for each experiment in the `MultiAssayExperiment` object. Names must match the `names(experiments(object))`. Passed to `matrixStats::weightedMedian` when aggregating feature scores per assay. Defaults to the sample size of an assay relative to the largest sample size when this paramter is missing.

The MultiAssayExperiment with the item featureRanks in the object metadata, which stores a DataFrame containing ranks accross all assays for each unique feature and the additional columns feature_score and feature_rank, as calculated with FUN and RANK_FUN, respectively. Information about which functions were used for each column can be found in the object mcols in the calculated_with column.

BiocGenerics::mad, dplyr::dense_rank, matrixStats::weightedMedian

bhklab/PanCuRx documentation built on Dec. 30, 2021, 4:59 p.m.