Nothing
R/autogating.R
In CytobankAPI: Cytobank API Wrapper for R
# Copyright 2020 Beckman Coulter, Inc.
# This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
# This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along with this program. If not, see <https://www.gnu.org/licenses/>.
#' Automatic gating Endpoints
#'
#' @name autogating
#' @param experiment_id integer representing an \link[=experiments]{experiment} ID
#' @param analysis_type character representing the type of ananlysis: auto_gate_train or auto_gate_inference
#' @param output character representing the output format \strong{[optional]}\cr
#' \emph{- drop.upload : \code{("default", "raw")}}\cr
#' \emph{- \code{dataframe}: converts the file internal compensation matrix output to a dataframe}
#' @param analysis_id integer representing the id of an autogating analysis
#' @param name character representing the name of an autogating analysis
#' @param fcsFileIds vector/list representing the id list of FCS files
#' @param gateSetIds vector/list representing the id list of Cytobank gate set
#' @param createBlindTestExperiment boolean A child experiment will be automatically created,
#' containing the subset of FCS files that were assigned to the blind test set.
#' For every predicted population, the files now contain one additional
#' parameter following the naming convention of auto_gate_Population name.
#' @param desiredEventsPerFile integer Only applies if eventSamplingMethod is set to equal. Defaults to 50,000.
#' It is the number of desired events to sample per file, but if the selected
#' population for any selected file has less total events than the specified number,
#' that quantity will be used instead.
#' @param desiredTotalEvents integer Only applies if eventSamplingMethod is set to proportional. Defaults to 5,000,000.
#' Represents the total desired number of events to sample amongst all selected files,
#' whilst keeping the numbers per file proportional to the total number of events in
#' the selected population for that file. If any file has less events in the selected
#' population than possible to make a perfectly proportional sampling to add up to the
#' desired total, all of the events in the file will be used instead.
#' @param eventSamplingMethod character Valid options are proportional, equal, or all. Defaults to equal.
#' If eventSamplingMethod is set to all, all events for the selected population
#' from all selected files will be used, without any further subsampling.
#' @param learningMagnification integer By increasing the magnification, the user can determine how many different
#' models are being trained using different parameters on the same training data.
#' The model with the highest KPI will be returned to the user.
#' With a magnification greater than 1, you may be able to influence the model
#' selection to return a model performing better on your population of interest,
#' but usually not significant. Of note, increasing the magnification also causes
#' a proportional increase of the runtime. It may also cause the run to crash
#' due to memory constraints if there are millions of events.
#' @param optimalClusters integer The best estimate of the number of distinct groups of files amongst those selected.
#' Usually, this aligns with how you would sample tag your files into different
#' conditions or time points. It helps the algorithm pick representative samples and
#' perform better. There is an option to create an experiment with blind test files and
#' their inferred populations. It can make it easier to visually evaluate model
#' performance.
#' @param randomSeed integer Accepts a positive integer value and sets a specific random seed to that value.
#' If this parameter is not specified or set to 0, autoSeed will automatically be set to true,
#' and a seed value will be randomly chosen, so that afterward it can be referred to for
#' reproducing the analysis results.
#' @param cloneGatesFromParent boolean The created child experiment will contain a copy of all gates & populations
#' already present in the parent experiment
#' @param trainedModelAnalysisId character The ID of the Autogate Training analysis that contains the model that
#' the inference run will use.
#' @param timeout integer representing the request timeout time in seconds \strong{[optional]}
#' @param UserSession Cytobank UserSession object
#'
#' @examples \dontrun{
#' # Create train analysis
#' autogating_train_analysis <- autogating.list_autogating_analyses_of_type(cyto_session,
#' p_experiment_id,
#' "auto_gate_train")
#' # Update train settings
#' autogating.update_autogating_training_analysis_details(cyto_session, p_experiment_id,
#' autogating_train_analysis$id,
#' FALSE, 39139, 100001, "proportional",
#' c(114386,114373,114383,114374,114384,114387,114385,114377,114382,114375),
#' c(4,3,1,11,10), 1, 2, 1)
#' # Run analysis
#' autogating.run_autogating_analysis(cyto_session, p_experiment_id, autogating_train_analysis$id)
#' # Create inference analysis
#' autogating_inference_analysis <- autogating.list_autogating_analyses_of_type(cyto_session,
#' p_experiment_id,
#' "auto_gate_inference")
#' # Update inference settings
#' autogating.update_autogating_inference_analysis_details(cyto_session, p_experiment_id,
#' autogating_inference_analysis$id, FALSE,
#' c(114376,114378,114379,114380,114381,114388,114389,114390),
#' autogating_train_analysis$id)
#' # Run analysis
#' autogating.run_autogating_analysis(cyto_session, p_experiment_id,
#' autogating_inference_analysis$id)
#' }
NULL
setGeneric("autogating.list_autogating_analyses_of_type",
function(UserSession, experiment_id, analysis_type, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.list_autogating_analyses_of_type")
})
#' @rdname autogating
#' @aliases autogating.list_autogating_analyses_of_type
#'
#' @details \code{autogating.list_autogating_analyses_of_type}
#' @examples \dontrun{autogating.list_autogating_analyses_of_type(cyto_session, 22, "auto_gate_train")
#' }
#' @export
setMethod("autogating.list_autogating_analyses_of_type", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_type, output="default", timeout=UserSession@long_timeout)
{
resp <- GET(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_type),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.show_autogating_analysis_details",
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.show_autogating_analysis_details")
})
#' @rdname autogating
#' @aliases autogating.show_autogating_analysis_details
#'
#' @details \code{autogating.show_autogating_analysis_details}
#' @examples \dontrun{autogating.show_autogating_analysis_details(cyto_session, 22, 10)
#' }
#' @export
setMethod("autogating.show_autogating_analysis_details", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
resp <- GET(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id,
"?include_settings=1"),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.create_autogating_analysis",
function(UserSession, experiment_id, analysis_type, name, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.create_autogating_analysis")
})
#' @rdname autogating
#' @aliases autogating.create_autogating_analysis
#'
#' @details \code{autogating.create_autogating_analysis} Create a new automatic gating analysis of
#' the specified type (auto_gate_train or auto_gate_inference).
#' @examples \dontrun{autogating.create_autogating_analysis(cyto_session, 22, "auto_gate_train",
#' "My auto gating train analysis")
#' }
#' @export
setMethod("autogating.create_autogating_analysis", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_type, name, output="default", timeout=UserSession@long_timeout)
{
resp <- POST(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_type),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
body=list(name = name),
encode="json",
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.update_autogating_training_analysis_details",
function(UserSession, experiment_id, analysis_id, createBlindTestExperiment, desiredEventsPerFile,
desiredTotalEvents, eventSamplingMethod, fcsFileIds, gateSetIds, learningMagnification,
optimalClusters, randomSeed, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.update_autogating_training_analysis_details")
})
#' @rdname autogating
#' @aliases autogating.update_autogating_training_analysis_details
#'
#' @details \code{autogating.update_autogating_training_analysis_details}
#' @examples \dontrun{autogating.update_autogating_training_analysis_details(
#' cyto_session, 22, 10, FALSE, 5000, 100000,
#' "proportional",
#' c(10, 11, 12, 13, 14, 15, 16, 17, 18, 19),
#' c(3, 4), 1, 2, NULL)
#' }
#' @export
setMethod("autogating.update_autogating_training_analysis_details", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, createBlindTestExperiment, desiredEventsPerFile,
desiredTotalEvents, eventSamplingMethod, fcsFileIds, gateSetIds, learningMagnification,
optimalClusters, randomSeed, output="default", timeout=UserSession@long_timeout)
{
body <- list(options =
list(createBlindTestExperiment = createBlindTestExperiment,
desiredEventsPerFile = desiredEventsPerFile,
desiredTotalEvents = desiredTotalEvents,
eventSamplingMethod = eventSamplingMethod,
fcsFileIds = fcsFileIds,
gateSetIds = gateSetIds,
learningMagnification = learningMagnification,
optimalClusters = optimalClusters,
randomSeed = randomSeed
))
resp <- PUT(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/auto_gate_train/",
analysis_id),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
body=body,
encode="json",
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.update_autogating_inference_analysis_details",
function(UserSession, experiment_id, analysis_id, cloneGatesFromParent, fcsFileIds, trainedModelAnalysisId,
output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.update_autogating_inference_analysis_details")
})
#' @rdname autogating
#' @aliases autogating.update_autogating_inference_analysis_details
#'
#' @details \code{autogating.update_autogating_inference_analysis_details}
#' @examples \dontrun{autogating.update_autogating_inference_analysis_details(
#' cyto_session, 22, 10, FALSE, c(21, 22, 23), 10)
#' }
#' @export
setMethod("autogating.update_autogating_inference_analysis_details", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, cloneGatesFromParent, fcsFileIds, trainedModelAnalysisId,
output="default", timeout=UserSession@long_timeout)
{
body <- list(options =
list(
cloneGatesFromParent = cloneGatesFromParent,
fcsFileIds = fcsFileIds,
trainedModelAnalysisId = trainedModelAnalysisId
))
resp <- PUT(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/auto_gate_inference/",
analysis_id),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
body=body,
encode="json",
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.delete_autogating_analysis",
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.delete_autogating_analysis")
})
#' @rdname autogating
#' @aliases autogating.delete_autogating_analysis
#'
#' @details \code{autogating.delete_autogating_analysis}
#' @examples \dontrun{autogating.delete_autogating_analysis(cyto_session, 22, 10)
#' }
#' @export
setMethod("autogating.delete_autogating_analysis", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, timeout=UserSession@long_timeout)
{
resp <- DELETE(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (http_error(resp))
{
error_parse(resp, "autogating")
}
return(paste("Autogating (ID=", analysis_id, ") successfully deleted.", sep=""))
})
setGeneric("autogating.copy_autogating_analysis_settings",
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.copy_autogating_analysis_settings")
})
#' @rdname autogating
#' @aliases autogating.copy_autogating_analysis_settings
#'
#' @details \code{autogating.copy_autogating_analysis_settings}
#' @examples \dontrun{autogating.copy_autogating_analysis_settings(cyto_session, 22, 10)
#' }
#' @export
setMethod("autogating.copy_autogating_analysis_settings", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
resp <- POST(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id,
"/copy_settings"),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.rename_autogating_analysis",
function(UserSession, experiment_id, analysis_id, name, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.rename_autogating_analysis")
})
#' @rdname autogating
#' @aliases autogating.rename_autogating_analysis
#'
#' @details \code{autogating.rename_autogating_analysis}
#' @examples \dontrun{autogating.rename_autogating_analysis(cyto_session, 22, 10, "New new of analysis")
#' }
#' @export
setMethod("autogating.rename_autogating_analysis", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, name, output="default", timeout=UserSession@long_timeout)
{
resp <- PUT(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id, "/rename"),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
body=list(name=name),
encode="json",
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.run_autogating_analysis",
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.run_autogating_analysis")
})
#' @rdname autogating
#' @aliases autogating.run_autogating_analysis
#'
#' @details \code{autogating.run_autogating_analysis}
#' @examples \dontrun{autogating.run_autogating_analysis(cyto_session, 22, 10)
#' }
#' @export
setMethod("autogating.run_autogating_analysis", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
resp <- POST(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id, "/run"),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.show_autogating_analysis_status",
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.show_autogating_analysis_status")
})
#' @rdname autogating
#' @aliases autogating.show_autogating_analysis_status
#'
#' @details \code{autogating.show_autogating_analysis_status}
#' @examples \dontrun{autogating.show_autogating_analysis_status(cyto_session, 22, 10)
#' }
#' @export
setMethod("autogating.show_autogating_analysis_status", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
resp <- GET(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id, "/status"),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
Try the CytobankAPI package in your browser
Any scripts or data that you put into this service are public.
CytobankAPI documentation built on April 21, 2023, 9:08 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# Copyright 2020 Beckman Coulter, Inc.
# This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
# This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along with this program. If not, see <https://www.gnu.org/licenses/>.
#' Automatic gating Endpoints
#'
#' @name autogating
#' @param experiment_id integer representing an \link[=experiments]{experiment} ID
#' @param analysis_type character representing the type of ananlysis: auto_gate_train or auto_gate_inference
#' @param output character representing the output format \strong{[optional]}\cr
#' \emph{- drop.upload : \code{("default", "raw")}}\cr
#' \emph{- \code{dataframe}: converts the file internal compensation matrix output to a dataframe}
#' @param analysis_id integer representing the id of an autogating analysis
#' @param name character representing the name of an autogating analysis
#' @param fcsFileIds vector/list representing the id list of FCS files
#' @param gateSetIds vector/list representing the id list of Cytobank gate set
#' @param createBlindTestExperiment boolean A child experiment will be automatically created,
#' containing the subset of FCS files that were assigned to the blind test set.
#' For every predicted population, the files now contain one additional
#' parameter following the naming convention of auto_gate_Population name.
#' @param desiredEventsPerFile integer Only applies if eventSamplingMethod is set to equal. Defaults to 50,000.
#' It is the number of desired events to sample per file, but if the selected
#' population for any selected file has less total events than the specified number,
#' that quantity will be used instead.
#' @param desiredTotalEvents integer Only applies if eventSamplingMethod is set to proportional. Defaults to 5,000,000.
#' Represents the total desired number of events to sample amongst all selected files,
#' whilst keeping the numbers per file proportional to the total number of events in
#' the selected population for that file. If any file has less events in the selected
#' population than possible to make a perfectly proportional sampling to add up to the
#' desired total, all of the events in the file will be used instead.
#' @param eventSamplingMethod character Valid options are proportional, equal, or all. Defaults to equal.
#' If eventSamplingMethod is set to all, all events for the selected population
#' from all selected files will be used, without any further subsampling.
#' @param learningMagnification integer By increasing the magnification, the user can determine how many different
#' models are being trained using different parameters on the same training data.
#' The model with the highest KPI will be returned to the user.
#' With a magnification greater than 1, you may be able to influence the model
#' selection to return a model performing better on your population of interest,
#' but usually not significant. Of note, increasing the magnification also causes
#' a proportional increase of the runtime. It may also cause the run to crash
#' due to memory constraints if there are millions of events.
#' @param optimalClusters integer The best estimate of the number of distinct groups of files amongst those selected.
#' Usually, this aligns with how you would sample tag your files into different
#' conditions or time points. It helps the algorithm pick representative samples and
#' perform better. There is an option to create an experiment with blind test files and
#' their inferred populations. It can make it easier to visually evaluate model
#' performance.
#' @param randomSeed integer Accepts a positive integer value and sets a specific random seed to that value.
#' If this parameter is not specified or set to 0, autoSeed will automatically be set to true,
#' and a seed value will be randomly chosen, so that afterward it can be referred to for
#' reproducing the analysis results.
#' @param cloneGatesFromParent boolean The created child experiment will contain a copy of all gates & populations
#' already present in the parent experiment
#' @param trainedModelAnalysisId character The ID of the Autogate Training analysis that contains the model that
#' the inference run will use.
#' @param timeout integer representing the request timeout time in seconds \strong{[optional]}
#' @param UserSession Cytobank UserSession object
#'
#' @examples \dontrun{
#' # Create train analysis
#' autogating_train_analysis <- autogating.list_autogating_analyses_of_type(cyto_session,
#' p_experiment_id,
#' "auto_gate_train")
#' # Update train settings
#' autogating.update_autogating_training_analysis_details(cyto_session, p_experiment_id,
#' autogating_train_analysis$id,
#' FALSE, 39139, 100001, "proportional",
#' c(114386,114373,114383,114374,114384,114387,114385,114377,114382,114375),
#' c(4,3,1,11,10), 1, 2, 1)
#' # Run analysis
#' autogating.run_autogating_analysis(cyto_session, p_experiment_id, autogating_train_analysis$id)
#' # Create inference analysis
#' autogating_inference_analysis <- autogating.list_autogating_analyses_of_type(cyto_session,
#' p_experiment_id,
#' "auto_gate_inference")
#' # Update inference settings
#' autogating.update_autogating_inference_analysis_details(cyto_session, p_experiment_id,
#' autogating_inference_analysis$id, FALSE,
#' c(114376,114378,114379,114380,114381,114388,114389,114390),
#' autogating_train_analysis$id)
#' # Run analysis
#' autogating.run_autogating_analysis(cyto_session, p_experiment_id,
#' autogating_inference_analysis$id)
#' }
NULL
setGeneric("autogating.list_autogating_analyses_of_type",
function(UserSession, experiment_id, analysis_type, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.list_autogating_analyses_of_type")
})
#' @rdname autogating
#' @aliases autogating.list_autogating_analyses_of_type
#'
#' @details \code{autogating.list_autogating_analyses_of_type}
#' @examples \dontrun{autogating.list_autogating_analyses_of_type(cyto_session, 22, "auto_gate_train")
#' }
#' @export
setMethod("autogating.list_autogating_analyses_of_type", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_type, output="default", timeout=UserSession@long_timeout)
{
resp <- GET(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_type),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.show_autogating_analysis_details",
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.show_autogating_analysis_details")
})
#' @rdname autogating
#' @aliases autogating.show_autogating_analysis_details
#'
#' @details \code{autogating.show_autogating_analysis_details}
#' @examples \dontrun{autogating.show_autogating_analysis_details(cyto_session, 22, 10)
#' }
#' @export
setMethod("autogating.show_autogating_analysis_details", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
resp <- GET(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id,
"?include_settings=1"),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.create_autogating_analysis",
function(UserSession, experiment_id, analysis_type, name, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.create_autogating_analysis")
})
#' @rdname autogating
#' @aliases autogating.create_autogating_analysis
#'
#' @details \code{autogating.create_autogating_analysis} Create a new automatic gating analysis of
#' the specified type (auto_gate_train or auto_gate_inference).
#' @examples \dontrun{autogating.create_autogating_analysis(cyto_session, 22, "auto_gate_train",
#' "My auto gating train analysis")
#' }
#' @export
setMethod("autogating.create_autogating_analysis", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_type, name, output="default", timeout=UserSession@long_timeout)
{
resp <- POST(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_type),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
body=list(name = name),
encode="json",
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.update_autogating_training_analysis_details",
function(UserSession, experiment_id, analysis_id, createBlindTestExperiment, desiredEventsPerFile,
desiredTotalEvents, eventSamplingMethod, fcsFileIds, gateSetIds, learningMagnification,
optimalClusters, randomSeed, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.update_autogating_training_analysis_details")
})
#' @rdname autogating
#' @aliases autogating.update_autogating_training_analysis_details
#'
#' @details \code{autogating.update_autogating_training_analysis_details}
#' @examples \dontrun{autogating.update_autogating_training_analysis_details(
#' cyto_session, 22, 10, FALSE, 5000, 100000,
#' "proportional",
#' c(10, 11, 12, 13, 14, 15, 16, 17, 18, 19),
#' c(3, 4), 1, 2, NULL)
#' }
#' @export
setMethod("autogating.update_autogating_training_analysis_details", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, createBlindTestExperiment, desiredEventsPerFile,
desiredTotalEvents, eventSamplingMethod, fcsFileIds, gateSetIds, learningMagnification,
optimalClusters, randomSeed, output="default", timeout=UserSession@long_timeout)
{
body <- list(options =
list(createBlindTestExperiment = createBlindTestExperiment,
desiredEventsPerFile = desiredEventsPerFile,
desiredTotalEvents = desiredTotalEvents,
eventSamplingMethod = eventSamplingMethod,
fcsFileIds = fcsFileIds,
gateSetIds = gateSetIds,
learningMagnification = learningMagnification,
optimalClusters = optimalClusters,
randomSeed = randomSeed
))
resp <- PUT(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/auto_gate_train/",
analysis_id),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
body=body,
encode="json",
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.update_autogating_inference_analysis_details",
function(UserSession, experiment_id, analysis_id, cloneGatesFromParent, fcsFileIds, trainedModelAnalysisId,
output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.update_autogating_inference_analysis_details")
})
#' @rdname autogating
#' @aliases autogating.update_autogating_inference_analysis_details
#'
#' @details \code{autogating.update_autogating_inference_analysis_details}
#' @examples \dontrun{autogating.update_autogating_inference_analysis_details(
#' cyto_session, 22, 10, FALSE, c(21, 22, 23), 10)
#' }
#' @export
setMethod("autogating.update_autogating_inference_analysis_details", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, cloneGatesFromParent, fcsFileIds, trainedModelAnalysisId,
output="default", timeout=UserSession@long_timeout)
{
body <- list(options =
list(
cloneGatesFromParent = cloneGatesFromParent,
fcsFileIds = fcsFileIds,
trainedModelAnalysisId = trainedModelAnalysisId
))
resp <- PUT(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/auto_gate_inference/",
analysis_id),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
body=body,
encode="json",
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.delete_autogating_analysis",
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.delete_autogating_analysis")
})
#' @rdname autogating
#' @aliases autogating.delete_autogating_analysis
#'
#' @details \code{autogating.delete_autogating_analysis}
#' @examples \dontrun{autogating.delete_autogating_analysis(cyto_session, 22, 10)
#' }
#' @export
setMethod("autogating.delete_autogating_analysis", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, timeout=UserSession@long_timeout)
{
resp <- DELETE(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (http_error(resp))
{
error_parse(resp, "autogating")
}
return(paste("Autogating (ID=", analysis_id, ") successfully deleted.", sep=""))
})
setGeneric("autogating.copy_autogating_analysis_settings",
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.copy_autogating_analysis_settings")
})
#' @rdname autogating
#' @aliases autogating.copy_autogating_analysis_settings
#'
#' @details \code{autogating.copy_autogating_analysis_settings}
#' @examples \dontrun{autogating.copy_autogating_analysis_settings(cyto_session, 22, 10)
#' }
#' @export
setMethod("autogating.copy_autogating_analysis_settings", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
resp <- POST(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id,
"/copy_settings"),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.rename_autogating_analysis",
function(UserSession, experiment_id, analysis_id, name, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.rename_autogating_analysis")
})
#' @rdname autogating
#' @aliases autogating.rename_autogating_analysis
#'
#' @details \code{autogating.rename_autogating_analysis}
#' @examples \dontrun{autogating.rename_autogating_analysis(cyto_session, 22, 10, "New new of analysis")
#' }
#' @export
setMethod("autogating.rename_autogating_analysis", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, name, output="default", timeout=UserSession@long_timeout)
{
resp <- PUT(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id, "/rename"),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
body=list(name=name),
encode="json",
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.run_autogating_analysis",
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.run_autogating_analysis")
})
#' @rdname autogating
#' @aliases autogating.run_autogating_analysis
#'
#' @details \code{autogating.run_autogating_analysis}
#' @examples \dontrun{autogating.run_autogating_analysis(cyto_session, 22, 10)
#' }
#' @export
setMethod("autogating.run_autogating_analysis", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
resp <- POST(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id, "/run"),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
setGeneric("autogating.show_autogating_analysis_status",
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
standardGeneric("autogating.show_autogating_analysis_status")
})
#' @rdname autogating
#' @aliases autogating.show_autogating_analysis_status
#'
#' @details \code{autogating.show_autogating_analysis_status}
#' @examples \dontrun{autogating.show_autogating_analysis_status(cyto_session, 22, 10)
#' }
#' @export
setMethod("autogating.show_autogating_analysis_status", signature(UserSession="UserSession"),
function(UserSession, experiment_id, analysis_id, output="default", timeout=UserSession@long_timeout)
{
resp <- GET(paste0(UserSession@site, "/experiments/", experiment_id, "/advanced_analyses/", analysis_id, "/status"),
add_headers(Authorization=paste("Bearer", UserSession@auth_token)),
timeout(timeout)
)
if (output == "default")
{
return(cyto_dataframe(parse(resp, "autogating")))
}
else # if (output == "raw")
{
return(parse(resp, "autogating"))
}
})
Try the CytobankAPI package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.