ConstructNetwork() Error in apply(scoreAll[modGenes[candidates], ], 1, which.max) : dim(X) must have a positive length

[QWDxxx]

hi,
I encountered an error when running the ConstructNetwork() function:
Error in apply(scoreAll[modGenes[candidates], ], 1, which.max) : dim(X) must have a positive length
Could it be because modGenes[candidates] is empty in my data? How should I adjust the previous data processing steps to make it run successfully? Although my Seurat object was converted from a Python AnnData object, I have completed the necessary preprocessing steps, including normalization. Additionally, my Seurat object already contains clustering results.

# preprocessing
mtx=readMM(".../sparse_matrix.mtx") 
cl=fread(".../cellinfo.csv",header = T,data.table = F )  
rl=fread(".../imm_geneinfo.csv",header = T,data.table = F)  
rownames(mtx)=rl$V1
colnames(mtx)=cl$index #paste0('c',cl$V2)
meta=cl
rownames(meta)=cl$index
identical(rownames(meta),colnames(mtx))
seurat_obj=CreateSeuratObject(counts = mtx  , 
                             meta.data = meta)
seurat_obj <- NormalizeData(seurat_obj, normalization.method = "LogNormalize", scale.factor = 10000)
seurat_obj <- FindVariableFeatures(seurat_obj, selection.method = "vst", nfeatures = 2000)
all.genes <- rownames(seurat_obj)
seurat_obj <- ScaleData(seurat_obj, features = all.genes)
seurat_obj <- RunPCA(seurat_obj, features = VariableFeatures(object = seurat_obj), npcs = 100)
seurat_obj <- RunHarmony(
  object = seurat_obj,
  group.by.vars = "sample",  
  reduction.use = "pca",      
  reduction.save = "harmony",
  dims = 1:100              
)
seurat_obj <- FindNeighbors(seurat_obj, reduction = 'harmony', dims = 1:90)
seurat_obj <- FindClusters(seurat_obj, resolution = 1.0)
seurat_obj <- RunUMAP(seurat_obj, dims = 1:90,reduction = 'harmony')

# step1
seurat_obj <- SetupForWGCNA(
  seurat_obj,
  gene_select = "fraction", 
  fraction = 0.05,         
  wgcna_name = "SPP1"     
)

# step2
seurat_obj <- MetacellsByGroups(
  seurat_obj = seurat_obj,
  group.by = c("imm_cell_type", "sample"), 
  reduction = 'harmony',              
  k = 25,                              
  max_shared = 10,                     
  ident.group = 'imm_cell_type'   
)

# step3
seurat_obj <- NormalizeMetacells(seurat_obj)

# step4
seurat_obj <- SetDatExpr(
  seurat_obj,
  group_name = "SPP1+Macrophage",    
  group.by = 'imm_cell_type', 
  assay = 'RNA',          
  slot = 'data'          
)

# step5
seurat_obj <- TestSoftPowers(
  seurat_obj,
  networkType = 'signed' 
) 

# step6
seurat_obj <- ConstructNetwork(
  seurat_obj,
  tom_name = 'SPP1_TOM', 
  soft_power = 6,
  setDatExpr=FALSE
)

Error in apply(scoreAll[modGenes[candidates], ], 1, which.max) : dim(X) must have a positive length
Looking forward to your advice; it will be of great help to me.
Thank you so much!