viSNE-class {CytobankAPI} | R Documentation |

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.

A Dimensionality Reduction advanced analysis object

`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

[Package *CytobankAPI* version 2.2.1 Index]