silhouetteRank_test: silhouetteRank_test

In bernard2012/Giotto: Spatial single-cell transcriptomics toolbox

Description

Previously: calculate_spatial_genes_python. This method computes a silhouette score per gene based on the spatial distribution of two partitions of cells (expressed L1, and non-expressed L0). Here, rather than L2 Euclidean norm, it uses a rank-transformed, exponentially weighted function to represent the local physical distance between two cells.

Usage

silhouetteRank_test(
  gobject,
  expression_values = c("normalized", "scaled", "custom"),
  subset_genes = NULL,
  overwrite_input_bin = TRUE,
  rbp_ps = c(0.95, 0.99),
  examine_tops = c(0.005, 0.01, 0.05, 0.1, 0.3),
  matrix_type = "dissim",
  num_core = 4,
  parallel_path = "/usr/bin",
  output = NULL,
  query_sizes = 10L
)

Arguments

gobject	giotto object
expression_values	expression values to use
subset_genes	only run on this subset of genes
overwrite_input_bin	overwrite input bin
rbp_ps	fractional binarization thresholds
examine_tops	top fractions to evaluate with silhouette
matrix_type	type of matrix
num_core	number of cores to use
parallel_path	path to GNU parallel function
output	output directory
query_sizes	size of query

Value

data.table with spatial scores

bernard2012/Giotto documentation built on Sept. 22, 2020, 10:29 a.m.