gates: Gate Endpoints

Description Usage Arguments Details Examples

Description

Interact with gate endpoints. In Cytobank there is a distinction between gates and populations. A gate is simply a shape drawn on a plot. A population is a set of gates and can have parents and children. Learn more about gates and populations. Currently, gate and population information can only be read and not written to Cytobank via the JSON API. To write gates and populations to Cytobank via the API, the gates.gatingML_upload endpoint should be used.

Usage

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## S4 method for signature 'UserSession'
gates.gatingML_download(
  UserSession,
  experiment_id,
  directory = getwd(),
  timeout = UserSession@long_timeout
)

## S4 method for signature 'UserSession'
gates.gatingML_upload(
  UserSession,
  experiment_id,
  file_path,
  timeout = UserSession@long_timeout
)

## S4 method for signature 'UserSession'
gates.apply(UserSession, experiment_id, timeout = UserSession@long_timeout)

## S4 method for signature 'UserSession'
gates.list(
  UserSession,
  experiment_id,
  output = "default",
  timeout = UserSession@short_timeout
)

## S4 method for signature 'UserSession'
gates.show(
  UserSession,
  experiment_id,
  gate_id,
  output = "default",
  timeout = UserSession@short_timeout
)

Arguments

UserSession

Cytobank UserSession object

experiment_id

integer representing an experiment ID

directory

character representing a specific directory to which the file will be downloaded (optional ending directory slash), if left empty, the default will be the current working directory [optional]

timeout

integer representing the request timeout time in seconds [optional]

file_path

character representing a file path

output

character representing the output format [optional]
- gates.list, gates.show : ("default", "raw")

gate_id

integer representing a gate ID

Details

gates.gatingML_download Download the gatingML from an experiment. Learn more about Gating-ML.

gates.gatingML_upload Upload a gatingML to an experiment. Learn more about Gating-ML.

gates.apply Apply gates as Experiment Gates. Gates must be applied in order for Scratch Gates to be converted to Experiment gates. Experiment gates are used for generating statistics, illustrations, and advanced analyses. Learn more about applying gates.

gates.list List all gates from an experiment. Outputs a dataframe [default] or raw list with all fields present. Currently only the Scratch Gates from the gating interface are returned. These have a version of -1. This is to be contrasted with Experiment Gates, which will have a version number that is a positive integer equal to the number of times the version has been incremented in the gating interface. Learn more about gate versioning in Cytobank.
- Optional output parameter, specify one of the following: ("default", "raw")

gates.show Show gate details from an experiment.

Examples

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## Not run: # Authenticate via username/password
cyto_session <- authenticate(site="premium", username="cyril_cytometry", password="cytobank_rocks!")
# Authenticate via auth_token
cyto_session <- authenticate(site="premium", auth_token="my_secret_auth_token")

## End(Not run)
## Not run: gates.gatingML_download(cyto_session, 22, directory="/my/new/download/directory/")

## Not run: gates.gatingML_upload(cyto_session, 22, file_path="/path/to/my_gatingML.xml")

## Not run: gates.apply(cyto_session, 22)

## Not run: # Dataframe of all gates with all fields present
gates.list(cyto_session, 22)

# Raw list of all gates with all fields present
gates.list(cyto_session, 22, output="raw")

## End(Not run)
## Not run: gates.show(cyto_session, 22, gate_id=2)

CytobankAPI documentation built on Oct. 4, 2021, 9:07 a.m.