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Hi, thank you for your great tools！ It is very useful to explore the interactions between different cell types. And I have a question about showning the plot. Can you add some other plots (such as sankey plot) to show the multiple networks？

Thank you so much for developing the tool!

I would like to know if in the LR-TF database you collected, are all LR's effects on TF activated? Is it possible that LR's effect on TF is inhibitory?

In addition, is the influence of TF on TG also positive? If it is not all positive, how should the situation be resolved?

Looking forward to your reply!

Hi scMLnet team. Thank you for bringing a such great tool for single cell analysis.

I encountered a problem while running RunMLnet function, see as below. It seems the rowMeans function can not work well here.

> netList <- RunMLnet(GCMat, BarCluFile, RecClu, LigClu, 
+                     pval, logfc, 
+                     LigRecLib, TFTarLib, RecTFLib)
[1] "check table cell:"
[1] 7978    2
[1] "Rec Cluster:"
[1] "Basal"
[1] "Lig Cluster:"
[1] "TCell"
[1] "p val:"
[1] 0.05
[1] "logfc:"
[1] 0.15
[1] "get High Exp Gene in Basal"
[1] "Basal:1744"
[1] "gene:31032"
[1] "logfc.threshold:"
[1] 0.15
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[1] "T-test in parallel"
[1] "find high gene num:2105"
[1] "-----------------------"
[1] "get High Exp Gene in TCell"
[1] "TCell:536"
[1] "gene:31032"
[1] "logfc.threshold:"
[1] 0.15
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[1] "T-test in parallel"
[1] "find high gene num:313"
[1] "-----------------------"
[1] "Lig_Rec Num:16"
[1] "TF_Target Num:727"
[1] "XZRec_XZTF Num:5469"
[1] "Rec common in LigRec and RecTF:"
[1] "TF common in RecTF and TFTar:"
[1] "calculate Cor between RecTF"
Error in rowMeans(GCMat[key_df$gene.1, ]) : 
  'x' must be an array of at least two dimensions

While I try to introduce a vector to rowMeans, it will show the same error such as:

> rowMeans(GCMat[1,])
Error in base::rowMeans(x, na.rm = na.rm, dims = dims, ...) : 
  'x' must be an array of at least two dimensions

Looking forward to any suggestion!

I ran this code with your example files:
netList <- RunMLnet(GCMat, BarCluFile, RecClu, LigClu,
pval, logfc,
LigRecLib, TFTarLib, RecTFLib)

I got this error :

Error in rowMeans(GCMat[key_df$gene.1, ]) :
'x' must be an array of at least two dimensions

I get the following error running RunMLnet, using the documented input formats:

head(control_meta_MLnet)
barcode assigned_cell_type
AAACCCAAGACAAGCC_1 AAACCCAAGACAAGCC_1 Fibroblast (1)
AAACCCAAGACTGTTC_1 AAACCCAAGACTGTTC_1 Fibroblast (1)
AAACCCAAGATACTGA_1 AAACCCAAGATACTGA_1 Macrophage, Dendritic (1)
AAACCCAAGCGTCGAA_1 AAACCCAAGCGTCGAA_1 Keratinocyte (1)
AAACCCAAGGAAGTGA_1 AAACCCAAGGAAGTGA_1 Macrophage, Dendritic (1)
AAACCCAAGGTCATCT_1 AAACCCAAGGTCATCT_1 Keratinocyte (1)

head(control_assay)

6 x 68364 sparse Matrix of class "dgCMatrix"
[[ suppressing 34 column names ‘AAACCCAAGACAAGCC_1’, ‘AAACCCAAGACTGTTC_1’, ‘AAACCCAAGATACTGA_1’ ... ]]

TMEM35A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
RIPPLY1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
ZNF157 . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
ARX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
PLS3 . . . . . . 1 . 1 . . 2 . . . 3 . . . . . . . . . . 2 . . . . 1 1 .
EMD . . 2 2 . . . . . 2 1 . . . 1 2 . . . . . . . 1 2 . . 1 1 3 3 1 . .

TMEM35A ......
RIPPLY1 ......
ZNF157 ......
ARX ......
PLS3 ......
EMD ......

.....suppressing 68330 columns in show(); maybe adjust 'options(max.print= *, width = *)'
..............................

netList <- RunMLnet(GCMat = control_assay,
BarCluFile = "control_meta_MLnet.txt",
RecClu = "Keratinocyte",
LigClu = "T-cell"
)
[1] "check table cell:"
[1] 0 2
[1] "Rec Cluster:"
[1] "Keratinocyte"
[1] "Lig Cluster:"
[1] "T-cell"
[1] "p val:"
[1] 0.05
[1] "logfc:"
[1] 0.15
[1] "get High Exp Gene in Keratinocyte"
[1] "Keratinocyte:0"
[1] "gene:15898"
Error in data.use[, cells, drop = F] :
invalid or not-yet-implemented 'Matrix' subsetting