Simulates various pieces of data for the purpose of demonstration in vignettes and help pages.
Usage
simulateExampleData(
n_pathways = 5000,
n_features = 15000,
n_samples = 8,
pathway_sizes = 15:500
)Value
A list of three elements:
- pathwaysList
A named list of dummy pathways. Names represent pathway identifiers; values represent character vectors of feature identifiers.
- featuresStat
A named numeric vector of dummy feature-wise statistics. Names represent feature identifiers; values represent 'scores' (e.g., log2 fold-change)
- summarizedexperiment
A SummarizedExperiment object that contains a count matrix with rownames and colnames.
Details
At least for the time being, this function generates dummy data purely for the purpose of demonstrating the format of expected inputs.
As such, the independent pieces of simulated data are just that – independent – in the meaning that simulated counts, statistics, and pathways are not related numerically, and do not make any biological sense.
The only coherent piece of information is the set of feature identifiers, carefully coordinated between the rownames of the count matrix, the names of the feature statistics, and the set of features in the list of pathways, so that panels in the app can transmit and interpret that shared piece of information.
Examples
set.seed(1)
simulated_data <- simulateExampleData()
head(lengths(simulated_data$pathwaysList))
#> pathway_1 pathway_2 pathway_3 pathway_4 pathway_5 pathway_6
#> 338 181 143 432 485 313
head(simulated_data$featuresStat)
#> feature_1 feature_2 feature_3 feature_4 feature_5 feature_6
#> 1.17063084 -1.39634072 0.07569717 0.22496577 -0.94038886 0.58330266