Returns a summary of lactate-mediated communication between cell types.
getLactateSignalingSummary(object, pathway = "combined", top_n = 10)data.frame summarizing top cell-cell communications
# \donttest{
data(crc_example)
obj <- createScMetaLink(crc_expr, crc_meta, "cell_type")
#> Created scMetaLink object with 4210 genes, 2850 cells, 15 cell types
obj <- inferLactateSignaling(obj)
#> Inferring lactate-mediated cell communication...
#> Cell types: 15
#> Direct pathway: TRUE
#> Indirect pathway: TRUE
#> Available lactate genes: 17/17
#> Calculating gene expression scores...
#> Calculating lactate production scores...
#> Calculating direct sensing scores (HCAR1)...
#> Calculating indirect sensing scores (GPR4/65/68/132)...
#> Normalizing scores...
#> Calculating direct communication scores...
#> Calculating indirect communication scores...
#> Running permutation test for direct pathway (100 permutations)...
#>
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#> Running permutation test for indirect pathway (100 permutations)...
#>
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#> Done!
#> Production scores for 15 cell types
#> Direct communication: 15 x 15 matrix
#> Indirect communication: 15 x 15 matrix
getLactateSignalingSummary(obj)
#> sender receiver communication_score rank
#> 1 Normal Macrophage TAM 1.5176455 1
#> 2 Normal Macrophage Normal Macrophage 1.4345244 2
#> 3 Normal Macrophage Pericyte 1.3311660 3
#> 4 Normal Macrophage Mast 1.2868515 4
#> 5 Normal Macrophage CAF 1.2522300 5
#> 6 Normal Macrophage Normal Fibroblast 1.2392587 6
#> 7 Normal Macrophage T 1.2179554 7
#> 8 Normal Macrophage Endothelial 1.2001152 8
#> 9 Normal Macrophage SMC 1.1799733 9
#> 10 Normal Macrophage B 0.7686704 10
# }