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
silhouetteRank( gobject, expression_values = c("normalized", "scaled", "custom"), metric = "euclidean", subset_genes = NULL, rbp_p = 0.95, examine_top = 0.3, python_path = NULL )
| 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 |
data.table with spatial scores