Create binSpect For Single Network

silhouetteRank()

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. New multi aggregator implementation can be found at `silhouetteRankTest() <silhouetteRankTest>`_

silhouetteRank(
    gobject,
    expression_values = c("normalized", "scaled", "custom"),
    metric = "euclidean",
    subset_genes = NULL,
    rbp_p = 0.95,
    examine_top = 0.3,
    python_path = NULL
)

Arguments

gobject	giotto object
expression_values	expression values to use
metric	distance metric to use
subset_genes	only run on this subset of genes
rbp_p	fractional binarization threshold
examine_top	top fraction to evaluate with silhouette
python_path	specify specific path to python if required

Value

A data.table with spatial scores.