Gene-regulatory network of pbmc

[watermelon-flower]

Dear,
Thank you for developed the scMEGA.I would like to ask you about the GRN inferred from the naïve CD4 T cells to memory CD4 T cells trajectory in the "Gene-regulatory network of CD4 T cells activaction" can be characterized as the GRN of all cells on the pbmc dataset？
thanks

[lzj1769]

Hi,

To you question, I dont think so.
To infer a GRN for all cells in PBMC, you need to use all of them.

[watermelon-flower]

Thank you, can I ignore the Trajectory analysis step and use all cells for TF and gene selection？

# Get a list of motif position frequency matrices from the JASPAR database
pfm <- getMatrixSet(
  x = JASPAR2020,
  opts = list(collection = "CORE", tax_group = 'vertebrates', all_versions = FALSE)
)

# add motif information
pbmc.all.cells <- AddMotifs(
  object = pbmc.all.cells,
  genome = BSgenome.Hsapiens.UCSC.hg38,
  pfm = pfm,
    assay = "ATAC"
)
# run chromVAR
pbmc.all.cells <- RunChromVAR(
  object = pbmc.all.cells,
  genome = BSgenome.Hsapiens.UCSC.hg38,
    assay = "ATAC"
)
sel.tfs <- SelectTFs(object = pbmc.all.cells, 
                 return.heatmap = TRUE,
                cor.cutoff = 0.4)
sel.genes <- SelectGenes(object = pbmc.all.cells,
                  labelTop1 = 0,
                  labelTop2 = 0)

Could you kindly advise me on how to modify the following code if I were to proceed without performing trajectory analysis?

tf.gene.cor <- GetTFGeneCorrelation(object = pbmc.all.cells, 
                                    tf.use = df.cor$tfs, 
                                    gene.use = unique(df.p2g$gene),
                                    tf.assay = "chromvar", 
                                    gene.assay = "RNA",
                                    trajectory.name = "Trajectory")

Could you kindly advise me on how to modify trajectory.name = "Trajectory" appropriately?
Thanks