get_num_batch_ranks: Plot factor-batch associations for increasing number of donor...

In scITD: Single-Cell Interpretable Tensor Decomposition

Plot factor-batch associations for increasing number of donor factors

Description

Plot factor-batch associations for increasing number of donor factors

Usage

get_num_batch_ranks(
  container,
  donor_ranks_test,
  gene_ranks,
  batch_var,
  thresh = 0.5,
  tucker_type = "regular",
  rotation_type = "hybrid"
)

Arguments

container	environment Project container that stores sub-containers for each cell type as well as results and plots from all analyses
donor_ranks_test	numeric The number of donor rank values to test
gene_ranks	numeric The number of gene ranks to use throughout
batch_var	character The name of the batch meta variable
thresh	numeric The threshold r-squared cutoff for considering a factor to be a batch factor. Can be a vector of multiple values to get plots at varying thresholds. (default=0.5)
tucker_type	character Set to 'regular' to run regular tucker or to 'sparse' to run tucker 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')

Value

A ggpubr figure of ggplot objects showing batch-factor associations and placed in container$plots$num_batch_factors slot

Examples

test_container <- get_num_batch_ranks(test_container, donor_ranks_test=c(2:4), 
gene_ranks=10, batch_var='lanes', thresh=0.5, tucker_type='regular', rotation_type='hybrid')

scITD documentation built on Sept. 8, 2023, 5:11 p.m.