Error in library(TCGA2STAT) : there is no package called ‘TCGA2STAT’ In addition: Warning message: replacing previous import ‘AUCell::cbind’ by ‘SingleCellExperiment::cbind’ when loading ‘SCENIC’ [1] "OVCAHs3" Warning: The 'show_progress' argument is deprecated as of v0.3. Use 'verbosity' instead. (in sctransform::vst) Calculating cell attributes from input UMI matrix: log_umi Variance stabilizing transformation of count matrix of size 14017 by 1661 Model formula is y ~ log_umi Get Negative Binomial regression parameters per gene Using 2000 genes, 1661 cells | | | 0% | |================== | 25% | |=================================== | 50% | |==================================================== | 75% | |======================================================================| 100% Found 41 outliers - those will be ignored in fitting/regularization step Second step: Get residuals using fitted parameters for 14017 genes | | | 0% | |== | 3% | |===== | 7% | |======= | 10% | |========== | 14% | |============ | 17% | |============== | 21% | |================= | 24% | |=================== | 28% | |====================== | 31% | |======================== | 34% | |=========================== | 38% | |============================= | 41% | |=============================== | 45% | 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corrected count matrix for 14017 genes | | | 0% | |== | 3% | |===== | 7% | |======= | 10% | |========== | 14% | |============ | 17% | |============== | 21% | |================= | 24% | |=================== | 28% | |====================== | 31% | |======================== | 34% | |=========================== | 38% | |============================= | 41% | |=============================== | 45% | |================================== | 48% | |==================================== | 52% | |======================================= | 55% | |========================================= | 59% | |=========================================== | 62% | |============================================== | 66% | |================================================ | 69% | |=================================================== | 72% | |===================================================== | 76% | |======================================================== | 79% | |========================================================== | 83% | |============================================================ | 86% | |=============================================================== | 90% | |================================================================= | 93% | |==================================================================== | 97% | |======================================================================| 100% Calculating gene attributes Wall clock passed: Time difference of 57.65079 secs Determine variable features Set 3000 variable features Place corrected count matrix in counts slot Centering data matrix | | | 0% | |==== | 5% | |======= | 11% | |=========== | 16% | |=============== | 21% | |================== | 26% | |====================== | 32% | |========================== | 37% | |============================= | 42% | |================================= | 47% | |===================================== | 53% | |========================================= | 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GJB2, KRT16, FOS, CTSB, DDIT4, SFN, PI3, TACSTD2, NR4A1 PC_ 2 Positive: COL1A2, SPARC, COL1A1, COL3A1, IGFBP7, CACNA1A, FN1, A2M, S100A8, COL4A1 S100A9, TIMP1, IGFBP3, SRGN, SPP1, COL6A3, VWF, MEG3, DUSP1, COL5A1 IGKC, NEAT1, LYZ, MGP, COL4A2, IGHA1, THY1, BGN, ZNF302, FOS Negative: EEF1A1, OLFM4, SCGB2A1, LTF, HPGD, VIM, FBLN1, TPPP3, SAT1, CAPS GRIA2, TMSB10, SLC25A35, CFAP157, SAXO2, TMEM178A, BAIAP3, LGR5, DOC2A, VWA3A CLU, DLEC1, DNAAF3, DNAJA4, CRACR2B, WDR35, MKI67, NUPL2, MDH1B, CCND2 PC_ 3 Positive: CACNA1A, ELF3, NR4A1, PGGHG, ZNF302, FOS, TNFAIP2, TCIM, KCNJ3, DUSP1 VEGFA, DUSP5, GREM1, ATF3, LIF, ZFP36, GADD45B, SLC25A37, MUC16, MALAT1 PLXNB1, DDIT4, RASD1, TOB1, WSB1, CCNL1, PTGS2, AL035078.1, CXCL1, MUC4 Negative: EEF1A1, TMSB10, S100A8, S100A9, SCGB2A1, S100A11, KRT6A, VIM, S100A10, S100A2 S100A6, ANXA1, KRT5, OLFM4, SPARC, IGFBP7, PERP, CSTA, FN1, LY6D FABP5, MT2A, FTL, KRT13, PLAT, DSG3, SLPI, A2M, COL4A1, HPGD PC_ 4 Positive: CACNA1A, KCNJ3, ZNF302, S100A9, S100A8, GMFB, KRT13, ANXA1, GREM1, CSTA KRT6A, SPRR1B, DEFB4A, SCEL, FOXP1, TMPRSS11E, LY6D, CALML5, FABP5, RHCG AL035078.1, LRRC69, SLC25A35, DSG3, TCN1, ARHGAP4, KRT5, NAMPT, DUOX2, RBM5 Negative: NR4A1, EEF1A1, SAT1, FOS, MMP7, ATF3, ZFP36, TCIM, DUSP1, DUSP5 PTGS2, LIF, IER3, KRT17, CCL20, FOSB, CXCL1, COL3A1, VEGFA, BTG2 SPARC, DDIT4, COL4A1, CLU, ELF3, CXCL2, CYR61, GADD45B, EGR1, CXCL5 PC_ 5 Positive: COL1A2, MEG3, S100A2, COL1A1, KRT5, PLAT, SFN, KRT17, COL3A1, FABP5 FN1, AEBP1, MMP10, COL7A1, CYR61, TNC, KRT6A, LUM, COL6A3, MT2A COL5A1, VCAN, IGFBP5, CTGF, EGR1, TFPI2, PDLIM7, LY6D, SERPINE1, ENC1 Negative: CXCL8, IGKC, IGHA1, SPP1, IGFBP3, CD55, SRGN, LYZ, LCN2, G0S2 IGHG3, CXCL5, IFITM2, CXCL1, FTL, IL1RN, SLPI, PTGS2, SAT1, VWF CCL20, LCP1, CD14, S100A9, C15orf48, NAMPT, A2M, HCK, TYROBP, ARRB2 Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation' This message will be shown once per session 10:10:29 UMAP embedding parameters a = 0.9922 b = 1.112 10:10:29 Read 1661 rows and found 10 numeric columns 10:10:29 Using Annoy for neighbor search, n_neighbors = 30 10:10:29 Building Annoy index with metric = cosine, n_trees = 50 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 10:10:29 Writing NN index file to temp file /tmp/RtmpiNt5DC/file414ea47ab9fde 10:10:29 Searching Annoy index using 1 thread, search_k = 3000 10:10:30 Annoy recall = 100% 10:10:31 Commencing smooth kNN distance calibration using 1 thread 10:10:32 Initializing from normalized Laplacian + noise 10:10:32 Commencing optimization for 500 epochs, with 67178 positive edges 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 10:10:40 Optimization finished null device 1 Computing nearest neighbor graph Computing SNN Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck Number of nodes: 1661 Number of edges: 57845 Running Louvain algorithm... 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Maximum modularity in 10 random starts: 0.7134 Number of communities: 8 Elapsed time: 0 seconds [1] 3000 1661 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 5 5 6 6 4 9 9 7 8 11 13 12 14 14 18 17 16 19 18 21 22 [1] "5" $m_CACNA1A [1] "CACNA1A" "KCNJ3" "GREM1" "ZNF302" "AL035078.1" [6] "PGGHG" "GMFB" "CXCL14" "ELF3" "LRRC69" [11] "FOXP1" "PLXNB1" "MALAT1" "NEUROD2" "CCNL1" [16] "RBM5" "SLC25A37" "GADD45B" "FILIP1" "NUMA1" [21] "TNFAIP2" "GRK2" "WSB1" "TBCD" "LAMA5" [26] "ID1" "PLXND1" "TMEM259" "HES1" "SPG7" [31] "WASHC1" "CHD3" "NDUFV1" "CTBP1" "AD000090.1" [36] "ARRDC3" "GGA1" "SGSM2" "SLITRK5" "AGRN" [41] "STAT2" "RHPN1" "AC026979.2" "ACCS" "NARF" [46] "LZTS2" "ARGLU1" "RBM25" "AKAP17A" "TUBGCP6" [51] "TSC2" "ACIN1" "PILRB" "SLC4A11" "CDK10" [56] "MAN2C1" "KAT2A" $m_S100A8 [1] "S100A8" "KRT17" "S100A9" "MMP7" "ANXA1" "KRT5" [7] "SLPI" "KRT6A" "NR4A1" "S100A2" "S100A6" "ATF3" [13] "SAT1" "LCN2" "FOS" "PLAT" "CTSB" "KRT16" [19] "CCL20" "CD55" "SFN" "LIF" "CSTB" "DUSP5" [25] "CXCL5" "PI3" "FABP5" "CXCL8" "TCIM" "TACSTD2" [31] "KRT13" "PERP" "PTGS2" "ZFP36" "TNC" "CXCL1" [37] "IER3" "LY6D" "DSG3" "SGK1" "S100A10" "DUSP1" [43] "F3" "GJB2" "DDIT4" "KRT14" "SERPINB1" "KRT19" [49] "S100A11" "GPNMB" "NDRG1" "CYP24A1" "SH3BGRL3" "CSTA" [55] "VEGFA" "MMP10" "DEPP1" "CDKN2B" "CXCL6" "CEACAM5" [61] "TMSB10" "TOB1" "RHCG" "CXCL2" "NFKBIA" "KRT6B" [67] "BHLHE40" "CRABP2" "PLAU" "BTG2" "STC1" "C3" $m_COL1A2 [1] "COL1A2" "COL1A1" "IGFBP7" "SPP1" "SPARC" "MEG3" "TIMP1" [8] "FN1" "COL3A1" "A2M" "FTL" "COL4A1" "IGFBP3" "SRGN" [15] "COL4A2" "ARHGAP4" "AEBP1" "COL6A3" "STAB1" "IGKC" "EGFL7" [22] "VCAN" "THBS1" "C1R" "COL5A1" "ID3" "LGALS1" "ENG" [29] "BGN" "IGFBP4" "HTRA1" "SLC2A3" "LYZ" "MGP" "LUM" [36] "G0S2" "TXNIP" "CALD1" "JAK3" "VWF" "IFITM2" "IGFBP5" [43] "MT2A" "NEAT1" "LAMA4" "CXCR4" "TYROBP" $m_EEF1A1 [1] "EEF1A1" "OLFM4" "SCGB2A1" "VIM" "HPGD" "TPPP3" "LTF" [8] "FBLN1" "GRIA2" "CCND2" $m_MIGA2 [1] "MIGA2" "ANAPC4" "PDCD11" "SETDB1" "BAP1" [6] "DGKD" "THBS3" "AKT1S1" "P2RY11" "CDK5RAP3" [11] "SLC25A25-AS1" "SH2B1" Warning message: Using `as.character()` on a quosure is deprecated as of rlang 0.3.0. Please use `as_label()` or `as_name()` instead. This warning is displayed once per session. null device 1 Calculating cluster 0 Calculating cluster 1 Calculating cluster 2 Calculating cluster 3 Calculating cluster 4 Calculating cluster 5 Calculating cluster 6 Calculating cluster 7 Warning message: CombinePlots is being deprecated. Plots should now be combined using the patchwork system. Calculating cluster m_CACNA1A Calculating cluster m_S100A8 Calculating cluster m_COL1A2 Calculating cluster m_EEF1A1 Calculating cluster m_MIGA2 Warning message: CombinePlots is being deprecated. Plots should now be combined using the patchwork system. null device 1