scenicOptions <- runSCENIC_3_scoreCells(scenicOptions, exprMat_log )
15:20 Step 3. Analyzing the network activity in each individual cell
Number of regulons to evaluate on cells: 12
Biggest (non-extended) regulons:
Junb (82g)
Fos (29g)
Irf7 (25g)
Stat1 (19g)
Fosb (11g)
Jun (12g)
Quantiles for the number of genes detected by cell:
(Non-detected genes are shuffled at the end of the ranking. Keep it in mind when choosing the threshold for calculating the AUC).
min 1% 5% 10% 50% 100%
6 8 9 10 12 16
Warning in .AUCell_calcAUC(geneSets = geneSets, rankings = rankings, nCores = nCores, :
Using only the first 8 genes (aucMaxRank) to calculate the AUC.
Error in .AUCell_calcAUC(geneSets = geneSets, rankings = rankings, nCores = nCores, :
Fewer than 20% of the genes in the gene sets are included in the rankings.Check wether the gene IDs in the 'rankings' and 'geneSets' match.
scenicOptions <- runSCENIC_3_scoreCells(scenicOptions, exprMat_log ) 15:20 Step 3. Analyzing the network activity in each individual cell Number of regulons to evaluate on cells: 12 Biggest (non-extended) regulons: Junb (82g) Fos (29g) Irf7 (25g) Stat1 (19g) Fosb (11g) Jun (12g) Quantiles for the number of genes detected by cell: (Non-detected genes are shuffled at the end of the ranking. Keep it in mind when choosing the threshold for calculating the AUC). min 1% 5% 10% 50% 100% 6 8 9 10 12 16 Warning in .AUCell_calcAUC(geneSets = geneSets, rankings = rankings, nCores = nCores, : Using only the first 8 genes (aucMaxRank) to calculate the AUC. Error in .AUCell_calcAUC(geneSets = geneSets, rankings = rankings, nCores = nCores, : Fewer than 20% of the genes in the gene sets are included in the rankings.Check wether the gene IDs in the 'rankings' and 'geneSets' match.