wrap_expression: Create a wrapper object with expression and counts

Description

Projected expression based on RNA velocity can also be added to the wrapper through the expression_future argument

Usage

wrap_expression(
  id = NULL,
  expression,
  counts,
  cell_info = NULL,
  feature_info = NULL,
  expression_future = NULL,
  ...
)

Arguments

id: A unique identifier for the data. If NULL, a random string will be generated.
expression: The normalised expression values of genes (columns) within cells (rows). This can be both a dense and sparse matrix.
counts: The counts values of genes (columns) within cells (rows). This can be both a dense and sparse matrix.
cell_info: Optional meta-information pertaining the cells.
feature_info: Optional meta-information of the features, a dataframe with at least feature_id as column
expression_future: Projected expression using RNA velocity of genes (columns) within cells (rows). This can be both a dense and sparse matrix.
...: extra information to be stored in the dataset

Details

Information about the cells and/or features can be added through cell_info and feature_info

Examples

Run this code

dataset <- wrap_expression(
  counts = example_dataset$counts,
  expression = example_dataset$expression,
  expression_future = example_dataset$expression_future
)

dataset$counts[1:10, 1:3]
dataset$expression[1:10, 1:3]
dataset$expression_future[1:10, 1:3]

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