Filter Interaction Changed Feature scores.
filterInteractionChangedFeats(
icfObject,
min_cells = 4,
min_cells_expr = 1,
min_int_cells = 4,
min_int_cells_expr = 1,
min_fdr = 0.1,
min_spat_diff = 0.2,
min_log2_fc = 0.2,
min_zscore = 2,
zscores_column = c("cell_type", "feats"),
direction = c("both", "up", "down")
)
filterICF(
icfObject,
min_cells = 4,
min_cells_expr = 1,
min_int_cells = 4,
min_int_cells_expr = 1,
min_fdr = 0.1,
min_spat_diff = 0.2,
min_log2_fc = 0.2,
min_zscore = 2,
zscores_column = c("cell_type", "feats"),
direction = c("both", "up", "down")
)ICF (interaction changed feature) score object
minimum number of source cell type
minimum expression level for source cell type
minimum number of interacting neighbor cell type
minimum expression level for interacting neighbor cell type
minimum adjusted p-value
minimum absolute spatial expression difference
minimum log2 fold-change
minimum z-score change
calculate z-scores over cell types or genes
differential expression directions to keep
icfObject that contains the filtered differential feature scores
g <- GiottoData::loadGiottoMini("visium")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> 3. read Giotto spatial information
#> 3.1 read Giotto spatial shape information
#> 3.2 read Giotto spatial centroid information
#> 3.3 read Giotto spatial overlap information
#> 4. read Giotto image information
#> python already initialized in this session
#> active environment : '/usr/bin/python3'
#> python version : 3.10
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#> "/usr/bin/python3"
icf <- findInteractionChangedFeats(g,
cluster_column = "leiden_clus",
selected_feats = c("Gna12", "Ccnd2", "Btbd17"),
nr_permutations = 10
)
#> Error: package 'future' is not yet installed
#>
#> To install:
#> install.packages(c("future"))
force(icf)
#> Error: object 'icf' not found
force(icf$ICFscores)
#> Error: object 'icf' not found
icf_filter1 <- filterInteractionChangedFeats(icf, min_cells = 4)
#> Error: object 'icf' not found
force(icf_filter1)
#> Error: object 'icf_filter1' not found
force(icf_filter1$ICFscores)
#> Error: object 'icf_filter1' not found
# filterICF is a simple alias with a shortened name
icf_filter2 <- filterICF(icf, min_cells = 4)
#> Error: object 'icf' not found
force(icf_filter2)
#> Error: object 'icf_filter2' not found