Coerce common R objects into a GDS — as

Provides a lightweight front door for external packages holding data in memory (lists, arrays, data.frames) to construct a validated GDS without going through on-disk adapters.

Usage

as_gds(x, ...)

# S3 method for class 'list'
as_gds(
  x,
  space = NULL,
  subjects = NULL,
  contrasts = NULL,
  col_data = NULL,
  row_data = NULL,
  metadata = list(),
  ...
)

# S3 method for class 'array'
as_gds(
  x,
  space = NULL,
  subjects = NULL,
  contrasts = NULL,
  assay_name = "beta",
  col_data = NULL,
  row_data = NULL,
  metadata = list(),
  ...
)

# S3 method for class 'data.frame'
as_gds(
  x,
  mapping = NULL,
  space = NULL,
  col_data = NULL,
  row_data = NULL,
  contrast_data = NULL,
  metadata = list(),
  ...
)

# S3 method for class 'nftab'
as_gds(x, feature = NULL, ...)

Arguments

x: Object to coerce (list/array/data.frame)
...: Additional arguments passed to methods
space: Optional space for sample axis; defaults to sample labels from data
subjects: Optional subject identifiers
contrasts: Optional contrast identifiers
col_data: Optional subject-level covariates
row_data: Optional sample-level metadata
metadata: Optional metadata list merged into gds_metadata()
assay_name: Name to use for the single-array input (default: "beta")
mapping: Optional list mapping column names for axes and assays. Default: list(sample="sample", subject="subject", contrast="contrast", assays=list(beta="beta", var="var"), contrast_data=NULL)
contrast_data: Optional contrast-level metadata. When omitted, mapping$contrast_data can name one or more long-table columns to collapse onto the contrast axis.
feature: Name of the neurotabs feature to use as the primary assay

Value

A gds object