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Construct a PhysioExperiment object

Source: R/PhysioExperiment-class.R
PhysioExperiment.Rd

Creates a new PhysioExperiment instance, which extends SummarizedExperiment with a samplingRate slot for physiological signal data.

Usage

PhysioExperiment(
  assays = S4Vectors::SimpleList(),
  rowData = NULL,
  colData = NULL,
  metadata = list(),
  samplingRate = as.numeric(NA),
  provenance = NULL
)

Arguments

assays

A SimpleList (or coercible object) of assay arrays.

rowData

Feature-level metadata as a DataFrame.

colData

Sample-level metadata as a DataFrame.

metadata

Optional experiment-level metadata list.

samplingRate

Numeric scalar sampling rate in Hz.

provenance

Optional. Either a character source identifier (e.g. a file path or dataset id) - in which case an initial PROV "import" activity recording wasDerivedFrom that source is seeded - or a pre-built provenance log (a list of entries) to attach. NULL (default) leaves the object with an empty audit trail. See provenance.

Value

A PhysioExperiment object containing the supplied assays, row/column metadata, and sampling rate.

References

Huber, W., et al. (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115-121. doi:10.1038/nmeth.3252

Morgan, M., et al. (2022). "S4Vectors: Foundation of vector-like and list-like containers in Bioconductor." R package.

See also

samplingRate for accessing the sampling rate, defaultAssay for retrieving the first assay name, channelInfo for channel metadata, setEvents for attaching event information

Examples

# Create a simple PhysioExperiment with random EEG-like data
# 1000 time points, 4 channels
eeg_data <- matrix(rnorm(1000 * 4), nrow = 1000, ncol = 4)
colnames(eeg_data) <- c("Fz", "Cz", "Pz", "Oz")

pe <- PhysioExperiment(
  assays = list(raw = eeg_data),
  colData = S4Vectors::DataFrame(
    label = c("Fz", "Cz", "Pz", "Oz"),
    type = rep("EEG", 4)
  ),
  samplingRate = 250
)
pe
#> class: PhysioExperiment
#> dim: 1000 x 4 
#> assays(1): raw
#> samplingRate: 250 Hz
#> channels(4): Fz, Cz, Pz, Oz
#> colData names(2): label, type

# Access sampling rate
samplingRate(pe)
#> [1] 250

# Create with multiple assays
pe2 <- PhysioExperiment(
  assays = list(raw = eeg_data, filtered = eeg_data * 0.5),
  samplingRate = 500
)