Beg you to help us reconstruct GRNs about cellnet HOT 1 OPEN

Hi Dan,

About training and query data

Both data are TPM matrices of genes. I found an error in these files. So I re-upload the files in my GitHub (https://github.com/AIBio/Pictures_for_Markdown/blob/master/CellNet_files.zip).

Here is my code to run CellNet:

grnProp <- cn_make_grn(sampTab = stAll, expDat = expAll[iGenes,], species = 'Mm', tfs = mmTFs, holmSpec = 1e-04)
cnProc <- cn_make_processor(expTrain = expAll, stTrain = stAll, ctGRNs = grnProp, dLevel = "description1", sidCol = "sample_id")
cnRes1 <- cn_apply(as.matrix(na.omit(all.ge.tpm[iGenes,])), all.meta.cellnet, cnProc, dLevelQuery = "sample_id")
bOrder <- c("Late2C", colnames(ge.tpm.raw$All_Toti)[1:14], "ICM")
cn_barplot_grnSing(cnRes0, cnProc, "ICM", c("Late2C", "ICM"), bOrder, sidCol = "sample_id")
rownames(all.meta.cellnet) <- as.vector(all.meta.cellnet$sample_id)
tfScores <- cn_nis_all(cnRes1, cnProc, "ICM")
plot_nis(tfScores, "ICM", all.meta.cellnet, "TLSCs.P12", dLevel = "description1", limitTo = 0)

Here is my code to run PACNet analysis:

Because I didn't have a GRN files for my samples. I have to reconstruct it. I have try to use the GRN file from CellNet output. But it didn't work.

grnAll <- utils_loadObject("CellNet_Rpks_output_grnProp_Mouse_pre-implantation_embryo_RS_Jul_08_2022.rda")
cnProc <- utils_loadObject("CellNet_Rpks_output_cnProc_Mouse_pre-implantation_embryo_RS_Jul_08_2022.rda")
grnAll <- grnAll
trainNormParam <- cnProc[8:12]
grnAll <- subsetGRNall(grnAll, iGenes)
trainNormParam <- subsetTrainNormParam(trainNormParam, grnAll, iGenes)
queryExpDat <- log(1+all.ge.tpm[iGenes,])
queryExpDat_ranked <- logRank(queryExpDat, base = 0)
GRN_statusQuery <- ccn_queryGRNstatus(expQuery = as.data.frame(queryExpDat_ranked), grn_return = grnAll, trainNorm = trainNormParam, classifier_return = my_classifier, prune = TRUE)

Here is my code to reconstruct GRNs with PACNet:

Since PACNet doesn't seem to support mouse data, I changed the code of the "ccn_makeGRN" function:

grnProp.pa <- ccn_makeGRN_new(expTrain = expAll[iGenes,], stTrain = stAll, species = "Mm", dLevel = "description1", dLevelGK = "description6")
trainNormParam <- ccn_trainNorm(expTrain = expAll[iGenes,], stTrain = stAll, subNets = grnProp[["ctGRNs"]][["geneLists"]],dLevel = "description1", sidCol = "sample_id")

Thank you again

Hanwen

Best wishes

from cellnet.