tSNE-class: S4 tSNE Class
In CytobankAPI: Cytobank API Wrapper for R

tSNE-class

R Documentation

S4 tSNE Class

Description

A tSNE object that holds pertinent tSNE advanced 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
auto_iterations: logical representing whether or not to set auto interations
auto_learning_rate: logical representing whether or not to set auto learning rate
clustering_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)
desired_events_per_file: numeric representing the number of desired events per file
desired_total_events: numeric representing the number of desired total events per file
early_exaggeration: numeric representing how tight natural clusters in the original space are in the embedded space and how much space will be between them
event_sampling_method: character representing the name of event sampling method will be used, learn more about Event Sampling for Dimensionality Reduction analysis
fcsfile_ids: list representing the fcs file ids
gateset_id: numeric representing the selected gate id
learning_rate: numeric representing the learning rate
normalize_scales: logical representing whether or not to normalize scales