Correct single-cell proteomics data

The function uses the data modelling output to generate corrected data that can be used for downstream analysis. The input is expected to be a SummarizedExperiment object that contains an estimated ScpModel. There are two approaches:

• scpKeepEffect(): keep the effects of interests. The reconstructed data is the sum of the effect matrices for the variable of interest and the residuals. Note that the intercepts (baseline intensity of each feature) are not included by default, but they can be added when intercept = TRUE.

• scpRemoveBatchEffect(): remove any undesired effect. The batch corrected data is the input data minus the effect matrices that correspond to batch effect variables. Note that the intercepts (baseline intensity of each feature) are removed by default, but they can be kept when intercept = FALSE.

Despite the two approaches are conceptually different, they can lead to similar results if the effects that are used to reconstruct the data are the ones that are not removed when performing batch correction (see examples).

The function returns a new SummarizedExperiment that contains an assay with the batch corrected data. Note that the 'ScpModel` is erased in this new object.

Usage

scpKeepEffect(object, effects = NULL, intercept = FALSE, name)

scpRemoveBatchEffect(object, effects = NULL, intercept = TRUE, name)

Arguments

object

An object that inherits from the SummarizedExperiment class. It must contain an estimated ScpModel in its metadata

effects

A character() vector. For scpKeepEffect(), which model variable should be used to reconstruct the data. For scpRemoveBatchEffect(), which model variable should be removed from the data. When NULL (default), both functions return the model residuals.

intercept

A logical(1). For scpKeepEffect(), should the intercepts be included when reconstructing the data? Defaults to FALSE, hence the intercepts are not included. For scpRemoveBatchEffect(), should the intercepts be removed from the data? Defaults to TRUE, hence the intercepts are removed from the data.

name

A character(1) providing the name to use to retrieve the model results. When retrieving a model and name is missing, the name of the first model found in object is used.

See also

• ScpModel for functions to extract information from the ScpModel object

• ScpModel-Workflow to run a model on SCP data required for batch correction.

Author

Christophe Vanderaa, Laurent Gatto

Examples

data("leduc_minimal")
scpModelFormula(leduc_minimal)
#> ~1 + Channel + Set + MedianIntensity + SampleType

reconstructed <- scpKeepEffect(leduc_minimal, effects = "SampleType")
batchCorreced <- scpRemoveBatchEffect(
    leduc_minimal, effects = c("Channel", "Set", "MedianIntensity")
)
## The two approaches are identical
identical(reconstructed, batchCorreced)
#> [1] TRUE