ggml_extract: Extract a feature-by-cell matrix from a single-cell container

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Extract a feature-by-cell matrix from a single-cell container

Description

Pulls an expression matrix out of a Seurat object, a SingleCellExperiment, a sparse dgCMatrix or a plain matrix, returning a dense numeric matrix with features in rows and cells in columns — the layout the GPU engine expects. Optional genes/cells subsetting happens before any sparse-to-dense materialisation.

Usage

ggml_extract(x, assay = NULL, layer = "data", genes = NULL, cells = NULL, ...)

## S3 method for class 'matrix'
ggml_extract(x, assay = NULL, layer = "data", genes = NULL, cells = NULL, ...)

## S3 method for class 'dgCMatrix'
ggml_extract(
  x,
  assay = NULL,
  layer = "data",
  genes = NULL,
  cells = NULL,
  keep_sparse = FALSE,
  ...
)

## S3 method for class 'Seurat'
ggml_extract(
  x,
  assay = NULL,
  layer = "data",
  genes = NULL,
  cells = NULL,
  keep_sparse = FALSE,
  ...
)

## S3 method for class 'SingleCellExperiment'
ggml_extract(
  x,
  assay = NULL,
  layer = "logcounts",
  genes = NULL,
  cells = NULL,
  keep_sparse = FALSE,
  ...
)

Arguments

x	A Seurat, SingleCellExperiment, dgCMatrix or matrix object.
assay	Assay to read from. Seurat: defaults to the object's default assay. Ignored for bare matrices.
layer	Layer / slot to read. Seurat v5: a layer name (default "data"); Seurat v4: mapped to the slot argument of GetAssayData. Ignored for bare matrices.
genes	Optional character/integer vector selecting feature rows.
cells	Optional character/integer vector selecting cell columns.
...	Passed to methods.
keep_sparse	If TRUE, return the (subset) dgCMatrix without densifying. Only the LogNormalize path (op = "normalize") sets this, since it transforms the stored non-zeros in place; every other op leaves it FALSE and gets a dense matrix as before.

Details

For a SingleCellExperiment the layer argument names an assay (default "logcounts", the log-normalised matrix); it is read with SummarizedExperiment::assay().

Value

A dense numeric matrix, features x cells.

ggmlR documentation built on July 14, 2026, 1:08 a.m.