viSNE-class {CytobankAPI}

S4 viSNE Class

Description

A viSNE object that holds pertinent viSNE analysis run information. This class should never be called explicitly. If a user would like to create a new Cytobank Dimensionality Reduction object, utilize the dimensionality_reduction.new function, or any other Dimensionality Reduction endpoints that return Dimensionality Reduction objects documented in the 'Details' section.

Value

A Dimensionality Reduction advanced analysis object

Slots

iterations

numeric representing the number of times Dimensionality Reduction processes the dataset using its step-wise optimization algorithm, learn more about how iterations affect Dimensionality Reduction results

perplexity

numeric representing a rough guess for the number of close neighbors any given cellular event will have, learn more about Dimensionality Reduction perplexity

channels

list the channels selected for the Dimensionality Reduction analysis, this can be either a list of short channel IDs (integer) OR long channel names (character)

compensation_id

the compensation ID selected for the Dimensionality Reduction analysis

population_selections

dataframe representing which population(s) data will be sourced, learn more about selecting populations for Dimensionality Reduction

sampling_total_count

numeric representing the total number of events to sample for the Dimensionality Reduction analysis

sampling_target_type

character representing the event sampling type
- choose one of the following : ("proportional", "equal")

seed

character representing the seed, Dimensionality Reduction picks a random seed each run, but if users want reproducible data, setting the same seed will allow them to do this

theta

numeric representing the balance of speed and accuracy in the Dimensionality Reduction run compared to the original tSNE algorithm, learn more about Dimensionality Reduction theta

visne_id

numeric representing the Dimensionality Reduction analysis ID