H5adResult

H5adResult

Pre-computed analysis results in the H5AD format.

Constructor

new H5adResult(h5File)

Source:
Parameters:
Name Type Description
h5File SimpleFile | string | Uint8Array | File

Contents of a H5AD file. On browsers, this may be a File object. On Node.js, this may also be a string containing a file path.

Classes

H5adResult

Methods

clear()

Description:

  • Destroy caches if present, releasing the associated memory. This may be called at any time but only has an effect if cache = true in load or summary.

Source:

load(optionsopt) → {object}

Source:
Parameters:
Name Type Attributes Default Description
options object <optional>
 {}

Optional parameters.

Properties
Name Type Attributes Default Description
cache boolean <optional>
 false

Whether to cache the results for re-use in subsequent calls to this method or summary. If true, users should consider calling clear to release the memory once this dataset instance is no longer needed.
Returns:

Object containing the per-feature and per-cell annotations. This has the following properties:

  • features: an object where each key is a modality name and each value is a DataFrame of per-feature annotations for that modality.
  • cells: a DataFrame containing per-cell annotations.
  • matrix: a MultiMatrix containing one ScranMatrix per modality.
  • reduced_dimensions: an object containing the dimensionality reduction results. Each value is an array of arrays, where each inner array contains the coordinates for one dimension.
Type
object

options() → {object}

Source:
Returns:

Object containing all options used for loading.

Type
object

setOptions(options)

Source:
Parameters:
Name Type Description
options object

Optional parameters that affect load (but not summary).

Properties
Name Type Attributes Default Description
primaryMatrixName string <optional>
<nullable>

Name of the layer containing the primary matrix. If null, the "X" dataset is used if it is present in the file, or the first available layer if no "X" dataset is present.
isPrimaryNormalized boolean <optional>

Whether the primary matrix is already normalized. If false, it is assumed to contain count data and is subjected to library size normalization within each modality.
featureTypeColumnName string <optional>
<nullable>

Name of the per-feature annotation column containing the feature types. If null, no column is assumed to contain the feature types, and all features are assumed to be genes (i.e., only the RNA modality is present).
reducedDimensionNames Array <optional>
<nullable>
 null

Array of names of the reduced dimensions to load. If null, all reduced dimensions found in the file are loaded.

summary(optionsopt) → {object}

Source:
Parameters:
Name Type Attributes Default Description
options object <optional>
 {}

Optional parameters.

Properties
Name Type Attributes Default Description
cache boolean <optional>
 false

Whether to cache the results for re-use in subsequent calls to this method or load. If true, users should consider calling clear to release the memory once this dataset instance is no longer needed.
Returns:

Object containing the per-feature and per-cell annotations. This has the following properties:

  • all_features: a DataFrame of per-feature annotations.
  • cells: a DataFrame of per-cell annotations.
  • all_assay_names: an Array of strings containing names of potential primary matrices.
  • reduced_dimension_names: an Array of strings containing names of dimensionality reduction results.
Type
object

(static) defaults() → {object}

Source:
Returns:

Default options, see setOptions for more details.

Type
object