View source: R/test_stability.R
run_stability_analysis | R Documentation |
Test stability of a decomposition by subsampling or bootstrapping donors. Note that running this function will replace the decomposition in the project container with one resulting from the tucker parameters entered here.
run_stability_analysis(
container,
ranks,
tucker_type = "regular",
rotation_type = "hybrid",
subset_type = "subset",
sub_prop = 0.75,
n_iterations = 100,
ncores = container$experiment_params$ncores
)
container |
environment Project container that stores sub-containers for each cell type as well as results and plots from all analyses |
ranks |
numeric The number of donor, gene, and cell type ranks, respectively, to decompose to using Tucker decomposition. |
tucker_type |
character The 'regular' type is the only one implemented with sparsity constraints (default='regular') |
rotation_type |
character Set to 'hybrid' to optimize loadings via our hybrid method (see paper for details). Set to 'ica_dsc' to perform ICA rotation on resulting donor factor matrix. Set to 'ica_lds' to optimize loadings by the ICA rotation. (default='hybrid') |
subset_type |
character Set to either 'subset' or 'bootstrap' (default='subset') |
sub_prop |
numeric The proportion of donors to keep when using subset_type='subset' (default=.75) |
n_iterations |
numeric The number of iterations to perform (default=100) |
ncores |
numeric The number of cores to use (default=container$experiment_params$ncores) |
The project container with the donor scores stability plot in container$plots$stability_plot_dsc and the loadings stability plot in container$plots$stability_plot_lds
test_container <- run_stability_analysis(test_container, ranks=c(2,4),
tucker_type='regular', rotation_type='hybrid', subset_type='subset',
sub_prop=0.75, n_iterations=5, ncores=1)
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