Aggregate an assay's quantitative features

This function aggregates the quantitative features of an assay, applying a summarization function (fun) to sets of features. The fcol variable name points to a rowData column that defines how to group the features during aggregate. This variable has to be an adjacency matrix. This function uses QFeatures::aggregateFeatures() to aggregate quantitative data.

The list of agregation methods can be obtained with the function aggregateMethods(). This function compiles both methods from the packages DaparToolshed and QFeatures.

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Usage

aggregateFeatures4Prostar(object, ...)

# S4 method for class 'QFeatures'
aggregateFeatures4Prostar(
  object,
  i,
  fcol,
  name = "newAssay",
  fun = MsCoreUtils::robustSummary,
  shared = TRUE,
  n = NULL,
  ...
)

# S4 method for class 'SummarizedExperiment'
aggregateFeatures4Prostar(
  object,
  fcol,
  fun = MsCoreUtils::robustSummary,
  conds,
  shared = TRUE,
  n = NULL,
  ...
)

aggQmetacell(qMeta, X, level, conds)

aggregateMethods()

Arguments

object

An instance of class QFeatures or SummarizedExperiment

...

Additional parameters passed the fun.

i

The index or name of the assay which features will be aggregated the create the new assay.

fcol

A character(1) naming a rowdata variable (of assay i in case of a QFeatures) defining how to aggregate the features of the assay. This variable is a (possibly sparse) matrix. See below for details.

name

A character(1) naming the new assay. Default is newAssay. Note that the function will fail if there's already an assay with name.

fun

A function used for quantitative feature aggregation. See details for examples.

shared

A boolean indication if shared peptides should be considered. If TRUE, shared peptides

n

A numeric(1) specifying the number of peptides to use for each protein. If NULL, all peptides are considered.

conds

A character() vector which is the names of conditions for each sample in the dataset.

qMeta

An object of class 'SummarizedExperiment'

X

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level

A character(1) which is the type of dataset

Value

A QFeatures object with an additional assay or a SummarizedExperiment object (or subclass thereof).

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Details

This function uses QFeatures::aggregateFeatures() to aggregate quantitative data.

Iterative aggregation function

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Quantitative metadata aggregation

The function to aggregate the quantitative metadata is aggQmetadat().

See also

The QFeatures vignette provides an extended example and the Aggregation vignette, for a complete quantitative proteomics data processing pipeline.

Examples

## ---------------------------------------
## An example QFeatures with PSM-level data
## ---------------------------------------
if (FALSE) { # \dontrun{
library(SummarizedExperiment)
data(ft, package='DaparToolshed')
ft

## Aggregate peptides into proteins
## using the adjacency matrix
feat1 <- aggregateFeatures4Prostar(object = ft,
i = 1,
name = 'aggregated',
fcol = 'adjacencyMatrix',
fun = 'colSumsMat')
feat1

assay(feat1[[1]])
assay(feat1[[2]])
aggcounts(feat1[[2]])
assay(feat1[[3]])
aggcounts(feat1[[3]])
rowData(feat1[[2]])
} # }
data(ft, package='DaparToolshed')
qMeta <- qMetacell(ft, 1)
X <- QFeatures::adjacencyMatrix(ft[[1]])
level <- typeDataset(ft[[1]])
conds <- SummarizedExperiment::colData(ft)$Condition
aggQmeta <- aggQmetacell(qMeta, X, level, conds)