rankFeatures-MultiAssayExperiment-method: Rank the Features in a 'MultiAssayExperiment' Object

In bhklab/PDATK: Pancreatic Ductal Adenocarcinoma Tool-Kit

Description

Rank the Features in a MultiAssayExperiment Object

Usage

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

Arguments

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.

Value

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.

See Also

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

bhklab/PDATK documentation built on Dec. 27, 2021, 7:46 a.m.