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Prepare Groups for Imputation

Source: R/group_imp.R
prep_groups.Rd

Normalize and validate a grouping specification for use with group_imp().

Usage

prep_groups(
  obj_cn,
  group,
  subset = NULL,
  min_group_size = 0,
  allow_unmapped = FALSE,
  seed = NULL
)

Arguments

obj_cn

Character vector of column names from the data matrix, usually colnames(obj).

group

Specification of how features should be grouped for imputation. Accepted formats are:

  • A character scalar naming a supported Illumina platform; see Note.

  • A long-format data.frame with columns group and feature.

  • A list-column data.frame with a feature list-column. Optional list-columns are aux, for auxiliary feature names, and parameters, for group-specific parameter lists.

subset

Optional character vector of feature names to impute. If NULL, all grouped features are imputed. Features in a group but not in subset are demoted to auxiliary columns for that group. Groups left with zero features after demotion are dropped with a message.

min_group_size

Integer or NULL. Minimum total number of columns per group, counting both features and auxiliary columns. Groups smaller than this are padded with randomly sampled columns from obj_cn. If NULL or 0, no padding is performed.

allow_unmapped

Logical. If FALSE, every column in colnames(obj) must appear in group. If TRUE, columns with no group assignment are left untouched and are not used as auxiliary columns.

seed

Integer, numeric, or NULL. Random seed used when padding small groups.

Value

A data frame of class slideimp_tbl containing:

  • group: original group labels, if provided, or sequential group labels.

  • feature: a list-column of character vectors containing feature names.

  • aux: a list-column of character vectors containing auxiliary names.

  • parameters: a list-column of per-group configuration lists.

Details

prep_groups() converts long-format or list-column group specifications into a validated slideimp_tbl, enforces feature and auxiliary-column set relationships, prunes dropped columns, and optionally pads small groups.

Let \(A\) be obj_cn and \(B\) be the union of all feature and auxiliary names in group. When allow_unmapped = FALSE, the function enforces \(A \subseteq B\): every matrix column must appear somewhere in the grouping specification.

Elements in \(B\) but not in \(A\), such as previously dropped probes, are pruned from each group. Groups left with zero features after pruning are removed with a diagnostic message.

See also

group_imp()

Examples

sim <- sim_mat(n = 10, p = 20)
prepped <- prep_groups(colnames(sim$input), sim$col_group)
prepped
#> # slideimp table: 2 x 4
#>   group          feature             aux parameters
#>  group1 <character [12]> <character [0]> <list [0]>
#>  group2  <character [8]> <character [0]> <list [0]>