add_dataset,ReactomeAnalysisRequest,ExpressionSet-method {ReactomeGSA} | R Documentation |
Adds a dataset to the analysis request
## S4 method for signature 'ReactomeAnalysisRequest,ExpressionSet' add_dataset(request, expression_values, name, type, comparison_factor, comparison_group_1, comparison_group_2, sample_data = NULL, additional_factors = NULL, overwrite = FALSE, ...)
request |
ReactomeAnalysisRequest. |
expression_values |
ExpressionSet. Here, the sample_data is automaticall extracted from the |
name |
character. Name of the dataset. This must be unique within one request. |
type |
character. The type of the dataset. Get available types using |
comparison_factor |
character. The name of the sample property to use for the main comparison. The sample properties
are either retrieved from |
comparison_group_1 |
character. Name of the first group within |
comparison_group_2 |
character. Name of the second group within |
sample_data |
data.frame (optional) data.frame containing the sample metadata of the |
additional_factors |
vector. Vector of additional sample properties that are used as blocking factors (if supported by the chosen analysis method) in the gene set analysis. |
overwrite |
boolean. If set to |
... |
Additional parameters passed to downstream functions. See the respective documentation of whether any additional parameters are supported. |
The ReactomeAnalysisRequest
object with the added dataset
Other add_dataset methods: add_dataset,ReactomeAnalysisRequest,DGEList-method
,
add_dataset,ReactomeAnalysisRequest,EList-method
,
add_dataset,ReactomeAnalysisRequest,data.frame-method
,
add_dataset
# create a request using Camera as an analysis library(ReactomeGSA.data) data(griss_melanoma_proteomics) library(methods) my_request <- ReactomeAnalysisRequest(method = "Camera") # since the expression_values object is a limma EList object, the sample_data is # retrieved from there # add the dataset my_request <- add_dataset(request = my_request, expression_values = griss_melanoma_proteomics, name = "Proteomics", type = "proteomics_int", comparison_factor = "condition", comparison_group_1 = "MOCK", comparison_group_2 = "MCM", additional_factors = c("cell.type", "patient.id"))