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] "OVCAHs1" 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 17197 by 1762 Model formula is y ~ log_umi Get Negative Binomial regression parameters per gene Using 2000 genes, 1762 cells | | | 0% | |================== | 25% | |=================================== | 50% | |==================================================== | 75% | |======================================================================| 100% Found 77 outliers - those will be ignored in fitting/regularization step Second step: Get residuals using fitted parameters for 17197 genes | | | 0% | |== | 3% | |==== | 6% | |====== | 9% | |======== | 11% | |========== | 14% | |============ | 17% | |============== | 20% | |================ | 23% | |================== | 26% | |==================== | 29% | |====================== | 31% | |======================== | 34% | |========================== | 37% | |============================ | 40% | 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|================================================================ | 91% | |================================================================== | 94% | |==================================================================== | 97% | |======================================================================| 100% Computing corrected count matrix for 17197 genes | | | 0% | |== | 3% | |==== | 6% | |====== | 9% | |======== | 11% | |========== | 14% | |============ | 17% | |============== | 20% | |================ | 23% | |================== | 26% | |==================== | 29% | |====================== | 31% | |======================== | 34% | |========================== | 37% | |============================ | 40% | |============================== | 43% | |================================ | 46% | |================================== | 49% | |==================================== | 51% | |====================================== | 54% | |======================================== | 57% | 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gene attributes Wall clock passed: Time difference of 57.16324 secs Determine variable features Set 3000 variable features Place corrected count matrix in counts slot Centering data matrix | | | 0% | |=== | 4% | |====== | 9% | |========= | 13% | |============ | 17% | |=============== | 22% | |================== | 26% | |===================== | 30% | |======================== | 35% | |=========================== | 39% | |============================== | 43% | |================================= | 48% | |===================================== | 52% | |======================================== | 57% | |=========================================== | 61% | |============================================== | 65% | |================================================= | 70% | |==================================================== | 74% | |======================================================= | 78% | |========================================================== | 83% | |============================================================= | 87% | |================================================================ | 91% | |=================================================================== | 96% | |======================================================================| 100% Set default assay to SCT There were 50 or more warnings (use warnings() to see the first 50) PC_ 1 Positive: CD9, CD24, WFDC2, STMN1, H3F3A, NPM1, DAPL1, CRABP1, SLPI, LDHB RAN, KRT19, TPI1, SNRPE, EPCAM, CP, MEST, ATP5MPL, MT1G, ATP5F1C CRABP2, MT1E, ACP1, CLDN4, HSP90AA1, SCNN1A, LAPTM4B, KRT18, TACSTD2, PCNA Negative: AEBP1, LUM, MMP11, TAGLN, RARRES2, COL1A1, ACTA2, PLAU, MMP2, SFRP4 FN1, POSTN, TIMP3, TPM2, LGALS1, BGN, HLA-B, MYL9, NBL1, COL6A3 COL1A2, COMP, THBS2, NNMT, COL11A1, SERPINF1, COL5A2, DCN, IGKC, SPARC PC_ 2 Positive: MMP11, TIMP3, AEBP1, TAGLN, PLAU, COL11A1, FN1, SFRP4, RARRES2, LUM POSTN, MYL9, THBS2, MMP2, TPM2, ANTXR1, ACTA2, COL1A1, ACTG2, NBL1 CTSK, COMP, DCN, HOPX, COL8A1, COL1A2, COL5A2, IGFBP5, CTGF, ISLR Negative: IGLC3, IGHG4, IGHG2, IGHG1, IGLC2, IGKC, IGHG3, JCHAIN, IGHA1, SSR4 MZB1, CD74, HLA-DRA, APOC1, IGHM, IGHA2, HLA-DPA1, LYZ, C1QB, IGLV1-51 IGLV6-57, HLA-DRB1, HLA-DPB1, C1QA, FOS, XBP1, ISG20, IGLC6, C1QC, TYROBP PC_ 3 Positive: IGHG4, IGHG1, IGKC, IGHG3, IGLC3, IGHG2, IGLC2, SSR4, IGHM, IGLV1-51 MZB1, SFRP2, RGS5, IGLV6-57, IGFBP7, POU2AF1, JCHAIN, IGLC6, IGLL5, XBP1 COL4A1, VWF, LAMP5, IGHGP, LAMB1, EGFL7, PLVAP, SPARCL1, COL4A2, DERL3 Negative: CD74, HLA-DRA, LYZ, HLA-DPA1, HLA-DPB1, CXCL9, HLA-DRB1, CXCL10, APOC1, SLPI IL32, C1QB, TYROBP, C1QA, CCL5, HLA-DQA1, CTSD, HLA-DRB5, HLA-A, TRBC2 C1QC, HLA-B, HLA-C, ITGB2, SPP1, LAPTM5, TNFAIP2, CD68, CCL2, HLA-DQB1 PC_ 4 Positive: IGHG1, IGLC2, IGHG4, IGLC3, PLAU, MMP11, FN1, IGHG2, LUM, IGLV1-51 SSR4, MZB1, RARRES2, C3, MMP2, IGLV6-57, IGLC6, IGHG3, EPYC, COL11A1 TIMP3, CTSK, IGFL2, DERL3, COMP, SLPI, IGHM, IGKC, AEBP1, APOC1 Negative: RGS5, EGFL7, PLVAP, A2M, VWF, MGP, SPARCL1, PDGFRB, CCL21, COL4A1 ESAM, CDH5, COL18A1, IGFBP7, GJA4, PLXDC1, MCAM, CD34, ENG, ID3 GNG11, PECAM1, PLXND1, ECSCR, CALCRL, NDUFA4L2, COL4A2, CD93, EPAS1, C7 PC_ 5 Positive: CRABP1, MT1G, LYZ, MEST, HLA-DRA, APOC1, HLA-DPB1, STMN1, HLA-DPA1, MEG3 MT1E, PCSK2, HLA-DRB1, HLA-DRB5, TYROBP, COL26A1, ACTA2, HMGN2, C1QB, HLA-DQA1 HLA-DQB1, IGHA2, C1QA, LDHB, MT1F, HLA-DQA2, FOS, SAMD11, TAGLN, C1QC Negative: SLPI, ISG15, LCN2, CP, IFIT1, TACSTD2, IFI27, IGLC2, TFPI2, MGP KRT19, KRT23, MX1, SST, IGFBP3, TNFSF10, S100A9, CXCL10, GPX3, IFIH1 IFIT3, TNFAIP2, MGST1, IFI6, VTCN1, CD24, OAS1, KRT7, IFIT2, MUC16 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 10:10:32 UMAP embedding parameters a = 0.9922 b = 1.112 10:10:32 Read 1762 rows and found 10 numeric columns 10:10:32 Using Annoy for neighbor search, n_neighbors = 30 10:10:32 Building Annoy index with metric = cosine, n_trees = 50 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 10:10:33 Writing NN index file to temp file /tmp/RtmpJlGCXv/file666255bae2b8d 10:10:33 Searching Annoy index using 1 thread, search_k = 3000 10:10:34 Annoy recall = 100% 10:10:34 Commencing smooth kNN distance calibration using 1 thread 10:10:36 Initializing from normalized Laplacian + noise 10:10:36 Commencing optimization for 500 epochs, with 75822 positive edges 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 10:10:45 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: 1762 Number of edges: 59942 Running Louvain algorithm... 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Maximum modularity in 10 random starts: 0.7550 Number of communities: 7 Elapsed time: 0 seconds [1] 3000 1762 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 5 6 7 8 9 10 11 12 13 13 14 14 15 16 14 16 15 18 18 19 22 [1] "13" $m_STMN1 [1] "STMN1" "WFDC2" "CRABP1" "DAPL1" "MT1G" "MEST" "CD9" [8] "NPM1" "LDHB" "H3F3A" "MT1E" "MT1H" "SNRPE" "HIF3A" [15] "RAN" "MSLN" "REC8" "FABP5" "MT1F" "HMGN2" "ATP5MPL" [22] "PTPRF" "PLXNB1" "PRAME" "PCNA" "EPCAM" "RBP1" "ATP5F1C" [29] "HDAC2" "TMSB15A" "HSPE1" $m_NR2F1 [1] "NR2F1" "MAPKBP1" "VWCE" "GIGYF1" "GOLGA8A" "HRAS" "CCNL1" [8] "PKD1" "MAN2B2" "MRI1" "SPRY1" "MDGA1" "PHKA2" "MLLT6" [15] "BTBD8" "PABPC1L" "MPV17L" "XIST" "SYT12" "UBE2B" "PRPF19" [22] "SNX33" "CYHR1" "UBAP1L" "CCPG1" $m_SLPI [1] "SLPI" "TACSTD2" "KRT19" "LCN2" "KRT17" "CP" [7] "KRT23" "TFPI2" "KRT7" "GPX3" "CD24" "S100A9" [13] "MGST1" "MUC16" "SST" "TNFAIP2" "CLDN1" "S100A14" [19] "NDRG1" "SLC40A1" "CLDN7" "KRT15" "VTCN1" "PDZK1IP1" [25] "SNCG" "GPRC5A" "MALL" "TM4SF1" "VAV3" "PFKP" [31] "ELF3" "FGFR3" "ITGB6" "MUC1" "SLC2A1" "PERP" [37] "KRT8" $m_RGS5 [1] "RGS5" "EGFL7" "PLVAP" "VWF" "CCL21" "A2M" [7] "SPARCL1" "ESAM" "PLXDC1" "MCAM" "CDH5" "PDGFRB" [13] "CD34" "COL4A1" "GJA4" "FLT4" "CD93" "NDUFA4L2" [19] "GNG11" "EPAS1" "PECAM1" "ADGRL4" "ECSCR" "PCDH12" [25] "HIGD1B" "ENG" "LHFPL6" "PLXND1" "CD36" "SHANK3" [31] "ROBO4" "COL18A1" "NOTCH4" "CXorf36" "CALCRL" "FLT1" [37] "AQP1" "IGFBP7" "TFPI" "ADCY4" "CLEC14A" "ID3" [43] "MGP" "TIE1" "RHOJ" "DLL4" "OAF" "COL4A2" [49] "CARMN" "HEYL" "EMCN" "BCL6B" "C7" "STOM" [55] "ACVRL1" "SEPT4" "RASIP1" "ENPEP" "CSPG4" "COL15A1" [61] "PGF" "COL5A3" "INSR" "NID1" $m_IGKC [1] "IGKC" "IGLC3" "IGHG4" "IGHG1" "IGLC2" [6] "IGHG2" "IGHG3" "JCHAIN" "IGHA1" "MZB1" [11] "IGHM" "SSR4" "IGLL5" "IGLV1-51" "XBP1" [16] "IGLV6-57" "IGLC6" "IGHA2" "PIM2" "ISG20" [21] "POU2AF1" "SEC11C" "CD79A" "IGHGP" "FAM30A" [26] "FKBP11" "TENT5C" "IGLV3-1" "DERL3" "FCRL5" [31] "BTG2" "IRF4" "P2RX1" "AC012236.1" "IGLC7" [36] "HERPUD1" "IGLV3-25" "ATP2A3" "SLAMF7" $m_CD74 [1] "CD74" "HLA-DRA" "HLA-DPA1" "HLA-DPB1" "C1QB" "HLA-DRB1" [7] "C1QA" "C1QC" "LYZ" "TYROBP" "APOC1" "CCL5" [13] "TRBC2" "HLA-DRB5" "HLA-DQA1" "CXCL9" "CTSD" "IL32" [19] "HLA-DQA2" "LAPTM5" "HLA-DMB" "ITGB2" "MS4A6A" "TRAC" [25] "HLA-DQB1" "CD68" "TRBC1" "AIF1" "CD52" "HLA-A" [31] "HLA-F" "CORO1A" "FCER1G" "CD48" "HLA-B" "CD2" [37] "CD14" "HLA-DMA" "HLA-C" "LSP1" "CAPG" "RASSF4" [43] "SRGN" "GZMK" "PTPRC" "LILRB4" "CD3E" "CTSS" [49] "SLCO2B1" "NKG7" "TMEM176B" "PLEK" "LCP1" "GMFG" [55] "RAC2" "FCGR3A" "ACP5" "CSF1R" "ALOX5AP" "IL18" [61] "ARHGDIB" "CD37" "TRAF3IP3" "HLA-E" "CD53" "IL10RA" [67] "FYB1" "GPNMB" "ZAP70" "CD84" "CD6" "TFEC" [73] "TMEM176A" "MYO1F" "GZMA" "LAIR1" "ADA2" $m_DUSP1 [1] "DUSP1" "FOS" "HSPA1A" "ZFP36" "SGK1" "CCL4L2" [7] "IER3" "NR4A1" "RGS1" "JUNB" "CCL3" "CCL4" [13] "RIN3" "IER2" "TIMP1" "G0S2" "SOCS3" "JUN" [19] "LIF" "APOBEC3C" "CCL3L1" "CMKLR1" "PLA2G4C" "RGS4" [25] "MS4A14" "SLC2A3" $m_MMP11 [1] "MMP11" "AEBP1" "LUM" "TAGLN" "PLAU" "SFRP4" [7] "RARRES2" "TIMP3" "MMP2" "POSTN" "COL1A1" "FN1" [13] "COL11A1" "ACTA2" "THBS2" "MYL9" "NBL1" "TPM2" [19] "COMP" "SERPINF1" "COL5A2" "LGALS1" "CTSK" "DCN" [25] "COL1A2" "NNMT" "COL8A1" "CXCL12" "COL6A3" "ANTXR1" [31] "CTHRC1" "ACTG2" "COL5A1" "SPARC" "SULF1" "VCAN" [37] "HTRA1" "COL6A1" "HOPX" "MRC2" "CHPF" "ISLR" [43] "COL12A1" "EPYC" "C1S" "LRP1" $m_SFRP2 [1] "SFRP2" "COL16A1" "SERPINE1" "LAMP5" "MALAT1" "IGFBP5" [7] "BGN" "LAMB1" "LRRC32" "LTBP2" "INHBA" "WISP1" $m_ISG15 [1] "ISG15" "MX1" "CXCL10" "OAS1" "IFIT3" "PARP14" [7] "OAS2" "IFIT1" "MX2" "RSAD2" "OAS3" "IFITM1" [13] "IFI44L" "IFIT2" "GBP1" "IFI44" "OASL" "PLSCR1" [19] "IFIH1" "DDX60L" "CMPK2" "IFI27" "BST2" "SAMHD1" [25] "TAP1" "IFI35" "IFI6" "WARS" "C19orf66" "DDX58" [31] "EPSTI1" "TNFSF10" "SLC15A3" "CCL2" "SPP1" "USP18" [37] "UBA7" "APOL6" "APOL2" "RARRES3" "SOD2" "RNF213" [43] "SAMD9L" "APOL1" "PSMB8" "HERC5" "TAP2" "NMI" [49] "STAT2" "GBP4" "LGALS9" "LAMP3" "CCL8" "TNFSF13B" [55] "PSMB9" "ITGA2" "PHF11" "GBP3" "NLRC5" "IRF1" [61] "XAF1" "GBP2" "BNIP3" "ATP10A" "TMEM140" "TRIM22" [67] "CSF1" "IRF7" "CLEC2B" "BLVRA" "PSMB8-AS1" $m_SLN [1] "SLN" "LPIN2" "SLC9A3R2" "TP53INP2" "RIN1" [6] "DCLK2" "SH3RF3" "ZMAT3" "PLPPR2" "CYSTM1" [11] "SEC24D" "KCTD12" "BDH2" "KIF26B" "AC107294.2" [16] "EVI2A" "PPP1R7" "RASL12" "GALNT5" "DACT3" [21] "AC027307.2" "SLC25A27" "ST6GAL1" "BCAT1" "APCDD1" $m_DZIP1 [1] "DZIP1" "ELN" "RUBCNL" "SLC6A6" "PNPLA6" "TFF3" "ZSWIM6" "PAPSS1" [9] "NKTR" "DPYSL2" $m_MAPKAPK2 [1] "MAPKAPK2" "MAN2C1" "COL7A1" "SBNO2" "MAPK8IP3" "NUMA1" [7] "SLC22A17" "TNKS1BP1" "IQSEC2" "SLC20A1" "LRRC14" "HSPG2" [13] "CLTB" "FMNL1" "DNM2" "P3H3" "MICALL2" "TCIRG1" [19] "SNED1" "ATAD3B" "MVP" "RHBDD3" 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 Warning message: CombinePlots is being deprecated. Plots should now be combined using the patchwork system. Calculating cluster m_STMN1 Calculating cluster m_SLPI Calculating cluster m_RGS5 Calculating cluster m_IGKC Calculating cluster m_CD74 Calculating cluster m_DUSP1 Calculating cluster m_MMP11 Calculating cluster m_SFRP2 Warning message: CombinePlots is being deprecated. Plots should now be combined using the patchwork system. null device 1