AdtNormalizationState

AdtNormalizationState

This step performs normalization and log-transformation on the QC-filtered ADT matrix from the CellFilteringState. It wraps the groupedSizeFactors and logNormCounts functions from scran.js.

Methods not documented here are not part of the stable API and should not be used by applications.

Classes

AdtNormalizationState

Methods

compute(parameters)

Description:

  • This method should not be called directly by users, but is instead invoked by runAnalysis.

Source:
Parameters:
Name Type Description
parameters object

Parameter object, equivalent to the adt_normalization property of the parameters of runAnalysis.

Properties
Name Type Description
remove_bias boolean

Whether to remove composition bias between cell subpopulations. This is done by clustering cells and computing median-based size factors between the average pseudo-cells for each cluster. Users can set this to false to speed up the compute.
num_pcs number

Number of PCs to use for creating a low-dimensional embedding for clustering. Only used if remove_bias = true.
num_clusters number

Number of clusters to create with k-means clustering. Only used if remove_bias = true.
Returns:

The object is updated with new results.

fetchNormalizedMatrix() → {external:ScranMatrix}

Source:
Returns:

A ScranMatrix object containing the normalized ADT values, available after running compute.

Type
external:ScranMatrix

fetchParameters() → {object}

Source:
Returns:

Object containing the parameters.

Type
object

fetchSizeFactors() → {Float64WasmArray}

Source:
Returns:

Array of length equal to the number of cells, containing the ADT-derived size factor for each cell in the (QC-filtered) dataset. This is available after running compute.

Type
Float64WasmArray