Visualizing Large-scale Copy Number Variation in Single-Cell RNA-Seq Expression Data

Installation

Installing

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("infercnv")

Optional extension

If you want to use the interactive heatmap visualization, please check the add-on packge R inferCNV_NGCHM after installing the packages tibble, tsvio and NGCHMR. To install optional packages, type the following in an R command window:

install.packages("tibble")

install.packages("devtools")
devtools::install_github("bmbroom/tsvio")
devtools::install_github("bmbroom/NGCHMR", ref="stable")
devtools::install_github("broadinstitute/inferCNV_NGCHM")

And download the NGCHM java application by typing the following in a regular shell:

wget http://tcga.ngchm.net/NGCHM/ShaidyMapGen.jar

Running InferCNV

Create the InferCNV Object

Reading in the raw counts matrix and meta data, populating the infercnv object

infercnv_obj = CreateInfercnvObject(
  raw_counts_matrix="../inst/extdata/oligodendroglioma_expression_downsampled.counts.matrix.gz",
  annotations_file="../inst/extdata/oligodendroglioma_annotations_downsampled.txt",
  delim="\t",
  gene_order_file="../inst/extdata/gencode_downsampled.EXAMPLE_ONLY_DONT_REUSE.txt",
  ref_group_names=c("Microglia/Macrophage","Oligodendrocytes (non-malignant)"))
## INFO [2024-12-27 04:30:50] Parsing matrix: ../inst/extdata/oligodendroglioma_expression_downsampled.counts.matrix.gz
## INFO [2024-12-27 04:30:52] Parsing gene order file: ../inst/extdata/gencode_downsampled.EXAMPLE_ONLY_DONT_REUSE.txt
## INFO [2024-12-27 04:30:52] Parsing cell annotations file: ../inst/extdata/oligodendroglioma_annotations_downsampled.txt
## INFO [2024-12-27 04:30:52] ::order_reduce:Start.
## INFO [2024-12-27 04:30:52] .order_reduce(): expr and order match.
## INFO [2024-12-27 04:30:52] ::process_data:order_reduce:Reduction from positional data, new dimensions (r,c) = 10338,184 Total=18322440.6799817 Min=0 Max=34215.
## INFO [2024-12-27 04:30:52] num genes removed taking into account provided gene ordering list: 399 = 3.8595473012188% removed.
## INFO [2024-12-27 04:30:52] -filtering out cells < 100 or > Inf, removing 0 % of cells
## WARN [2024-12-27 04:30:53] Please use "options(scipen = 100)" before running infercnv if you are using the analysis_mode="subclusters" option or you may encounter an error while the hclust is being generated.
## INFO [2024-12-27 04:30:53] validating infercnv_obj

Running the full default analysis

out_dir = tempfile()
infercnv_obj_default = infercnv::run(
    infercnv_obj,
    cutoff=1, # cutoff=1 works well for Smart-seq2, and cutoff=0.1 works well for 10x Genomics
    out_dir=out_dir,
    cluster_by_groups=TRUE, 
    plot_steps=FALSE,
    denoise=TRUE,
    HMM=FALSE,
    no_prelim_plot=TRUE,
    png_res=60
)
## Warning: Data is of class matrix. Coercing to dgCMatrix.
## Finding variable features for layer counts
## Centering and scaling data matrix
## PC_ 1 
## Positive:  PSMD14, GCA, TANK, SCN2A, MARCH7, CSRNP3, TTC21B, SCN1A, SPC25, DHRS9 
##     BBS5, FASTKD1, PPIG, AKIRIN1, NDUFS5, RRAGC, MACF1, UTP11L, PPIEL, PHOSPHO2 
##     FHL3, PABPC4, SF3A3, PPIE, INPP5B, KLHL23, TRIT1, C1orf122, CAP1, MANEAL 
## Negative:  PPM1A, DHRS7, MNAT1, TRMT5, SLC38A6, HIF1A, SNAPC1, LINC00643, PCNXL4, DDHD1 
##     FERMT2, WDR89, GNPNAT1, GMFB, PPP2R5E, CGRRF1, STYX, RTN1, SOCS4, PSMC6 
##     MAPK1IP1L, FBXO34, ATG14, TXNDC16, JKAMP, KTN1, L3HYPDH, PELI2, C14orf166, KIAA0586 
## PC_ 2 
## Positive:  TMEM219, KCTD13, ASPHD1, TAOK2, SEZ6L2, HIRIP3, CDIPT, ALDOA, MVP, PAGR1 
##     PPP4C, PRRT2, MAZ, YPEL3, KIF22, QPRT, MAPK3, SULT1A4, SLX1B, CORO1A 
##     BOLA2, BOLA2B, SPNS1, SLX1A, NFATC2IP, SULT1A3, TUFM, CD2BP2, ATXN2L, TBC1D10B 
## Negative:  SEL1L, DIO2, NRXN3, ADCK1, GALC, SNW1, SPATA7, SLIRP, ZC3H14, ALKBH1 
##     TTC8, SPTLC2, FOXN3, AHSA1, EFCAB11, VIPAS39, TMED8, PSMC1, GSTZ1, POMT2 
##     CALM1, ZDHHC22, KIAA1737, RPS6KA5, ANGEL1, VASH1, C14orf159, GPATCH2L, TGFB3, SMEK1 
## PC_ 3 
## Positive:  CAND1, TMBIM4, DYRK2, MDM1, NUP107, RAP1B, LLPH, SLC35E3, LEMD3, MDM2 
##     CPM, GNS, CPSF6, LYZ, TBK1, YEATS4, XPOT, FRS2, C12orf66, SRGAP1 
##     CCT2, TMEM5, PPM1H, MON2, RAB3IP, USP15, CTDSP2, CNOT2, TSFM, METTL1 
## Negative:  RPL23A, SUPT6H, TRAF4, SDF2, FAM222B, KIAA0100, ALDOC, PIGS, ARHGEF26, ARHGEF26-AS1 
##     RAP2B, P2RY1, RNPC3, DPH5, MBNL1, SLC30A7, SLC44A1, ABCA1, FSD1L, EXTL2 
##     NIPSNAP3A, FKTN, RTCA, TMEM38B, HIAT1, P2RY12, SMC2, SLC35A3, ZNF462, KLF4 
## PC_ 4 
## Positive:  MRPL46, NTRK3, KLHL25, AKAP13, MRPS11, DET1, AEN, MFGE8, ABHD2, POLG 
##     PEX11A, AP3S2, IDH2, C15orf38-AP3S2, C15orf38, CIB1, NGRN, CRTC3, MAN2A2, UNC45A 
##     HDDC3, VPS33B, CHD2, RGMA, IGF1R, LRRC28, MEF2A, LINS, ASB7, VIMP 
## Negative:  RBM12, NFS1, CPNE1, ROMO1, ERGIC3, CEP250, EIF6, RBM39, EDEM2, TRPC4AP 
##     PHF20, GSS, SCAND1, ACSS2, LINC00657, GGT7, EPB41L1, TP53INP2, AAR2, NCOA6 
##     DLGAP4, PIGU, C20orf24, NDRG3, MAP1LC3A, SOGA1, DYNLRB1, SAMHD1, ITCH, RBL1 
## PC_ 5 
## Positive:  STX17, ERP44, NR4A3, INVS, SEC61B, TEX10, ALG2, MSANTD3, MSANTD3-TMEFF1, TGFBR1 
##     LPPR1, TBC1D2, MRPL50, TRIM14, ZNF189, NANS, ANP32B, TMEM246, C9orf156, RNF20 
##     XPA, SMC2, NCBP1, NIPSNAP3A, TSTD2, ABCA1, TMOD1, SLC44A1, ZNF510, FSD1L 
## Negative:  ZNF160, ZNF415, ZNF83, ZNF331, MYADM, ZNF528, NDUFA3, ZNF880, ZNF610, ZNF480 
##     TFPT, PRPF31, LENG1, MBOAT7, TSEN34, RPS9, LILRA4, LAIR1, TTYH1, LENG8 
##     LILRB4, RDH13, HSPBP1, RPL28, SHISA7, ISOC2, ZNF580, ZNF581, ZNF542, ZNF583
## Computing nearest neighbor graph
## Computing SNN
## Warning: Data is of class matrix. Coercing to dgCMatrix.
## Finding variable features for layer counts
## Centering and scaling data matrix
## PC_ 1 
## Positive:  RFC1, RPL9, KLHL5, LIAS, UGDH, TMEM156, UGDH-AS1, TLR1, KLF3, SMIM14 
##     PGM2, RELL1, UBE2K, ARAP2, TBC1D19, PDS5A, RBPJ, APBB2, ANAPC4, DHX15 
##     UCHL1, PACRGL, LCORL, DCAF16, LIMCH1, MED28, LAP3, TMEM33, QDPR, TAPT1-AS1 
## Negative:  PNPLA2, RPLP2, CD151, PIDD, SLC25A22, CEND1, POLR2L, PDDC1, TALDO1, CHID1 
##     TMEM80, TOLLIP, DEAF1, IRF7, MOB2, PHRF1, SNHG9, RPS2, IFITM10, TBL3 
##     NDUFB10, NTHL1, MSRB1, FAHD1, NUBP2, HAGH, SPSB3, MRPS34, TSC2, CRAMP1L 
## PC_ 2 
## Positive:  APC2, C19orf25, MBD3, UQCR11, SCAMP4, BTBD2, MOB3A, AP3D1, PLEKHJ1, RNPS1 
##     ECI1, E4F1, ABCA3, TBC1D24, ATP6V0C, MLST8, TRAF7, AMDHD2, SF3A2, PKD1 
##     TSC2, NTHL1, TBL3, SNHG9, CEMP1, RPS2, NDUFB10, OAZ1, MSRB1, FAHD1 
## Negative:  ZNF131, NIM1, NIPBL, SLC1A3, SEPP1, HMGCS1, SKP2, C5orf42, FBXO4, LMBRD2 
##     C5orf28, C5orf51, NUP155, BRIX1, PAIP1, WDR70, RAD1, OXCT1, NNT, LIFR 
##     AMACR, RPL37, RICTOR, TARS, FYB, MRPS30, DAB2, PRKAA1, SUB1, TTC33 
## PC_ 3 
## Positive:  PSMC5, TEX2, CCDC47, POLG2, FTSJ3, STRADA, DDX42, DDX5, TACO1, MIR3064 
##     MIR5047, DCAF7, CEP95, TANC2, SMURF2, PLEKHM1P, METTL2A, LRRC37A3, MED13, AMZ2P1 
##     INTS2, BCAS3, GNA13, PRKCA, PPM1D, CACNG4, APPBP2, HELZ, PSMD12, USP32 
## Negative:  PODXL2, MCM2, TPRA1, MGLL, PLXNA1, SEC61A1, CHCHD6, ZXDC, RUVBL1, SLC41A3 
##     CCDC14, KALRN, OSBPL11, UMPS, SNX4, ZNF148, EEFSEC, MYLK, PTPLB, RPN1 
##     SEC22A, RAB7A, SEMA5B, ACAD9, HSPBAP1, ISY1, DTX3L, CNBP, PARP9, COPG1 
## PC_ 4 
## Positive:  MOSPD3, ACTL6B, GNB2, GIGYF1, TSC22D4, POP7, C7orf61, MEPCE, ZCWPW1, SLC12A9 
##     PILRA, PILRB, TRIP6, SRRT, ACHE, AP1S1, PLOD3, ZNHIT1, FIS1, RABL5 
##     CUX1, PRKRIP1, ORAI2, ALKBH4, NDN, MKRN3, SNRPN, SNURF, HERC2P7, UBE3A 
## Negative:  SYNJ2BP, MED6, COX16, SMOC1, SRSF5, PCNX, KIAA0247, ZFYVE1, RBM25, PSEN1 
##     NUMB, ACOT2, PNMA1, ELMSAN1, PTGR2, CRY1, MTERFD3, ZNF410, C12orf23, RIC8B 
##     POLR3B, FAM161B, TCP11L2, CKAP4, COQ6, C12orf75, ALDH6A1, APPL2, LIN52, ABCD4 
## PC_ 5 
## Positive:  FGFR1OP, RNASET2, RPS6KA2, MLLT4, MPC1, SFT2D1, THBS2, QKI, C6orf120, CAHM 
##     LINC00574, AGPAT4, DLL1, FAM120B, MAP3K4, PSMB1, TBP, LPAL2, PDCD2, MRPL18 
##     TCP1, SRD5A1, MTRR, NSUN2, CCDC127, MED10, SDHA, FASTKD3, MRPL36, PDCD6 
## Negative:  SEC61B, NR4A3, ALG2, STX17, TGFBR1, TBC1D2, ERP44, TRIM14, NANS, INVS 
##     ANP32B, ECHDC1, RNF146, TEX10, KIAA0408, TRMT11, HINT3, NCOA7, C9orf156, MSANTD3 
##     PTPRK, MSANTD3-TMEFF1, EPB41L2, XPA, LPPR1, AKAP7, MRPL50, ZNF189, TMEM246, NCBP1
## Computing nearest neighbor graph
## Computing SNN
## Warning: Data is of class matrix. Coercing to dgCMatrix.
## Finding variable features for layer counts
## Centering and scaling data matrix
## PC_ 1 
## Positive:  NTHL1, TBL3, SNHG9, RPS2, NDUFB10, MSRB1, FAHD1, HAGH, NUBP2, SPSB3 
##     MRPS34, NME3, MAPK8IP3, CRAMP1L, TELO2, CLCN7, C16orf91, UNKL, GNPTG, BAIAP3 
##     UBE2I, SOX8, LMF1, CHTF18, RPUSD1, NARFL, HAGHL, WSCD1, MIS12, C1QBP 
## Negative:  NFASC, MDM4, CNTN2, PIK3C2B, RBBP5, PPP1R15B, DSTYK, TMCC2, SNRPE, ZBED6 
##     CDK18, ZC3H11A, NUCKS1, ATP2B4, RAB7L1, BTG2, SLC41A1, ADORA1, SRGAP2, TMEM183A 
##     GLMN, BTBD8, RPAP2, CDC7, ZNF644, RPL5, ZNF326, CYB5R1, LRRC8D, EIF2D 
## PC_ 2 
## Positive:  GBA2, CREB3, TLN1, CCDC107, RUSC2, STOML2, PIGO, FANCG, VCP, DNAJB5 
##     IL11RA, KIAA1161, FAM219A, GALT, NUDT2, RPP25L, DCTN3, SIGMAR1, UBAP1, ATP5H 
##     ARMC7, DCAF12, ICT1, NT5C, HN1, UBAP2, CDR2L, SUMO2, HID1, UBE2R2 
## Negative:  CD27-AS1, TNFRSF1A, TAPBPL, VAMP1, NACA, MRPL51, PRIM1, SNORA48, PARP11, LRP1 
##     TULP3, RHNO1, SHMT2, NRIP2, R3HDM2, ITFG2, FKBP4, ARHGAP9, DCP1B, MARS 
##     ADIPOR2, DDIT3, ERC1, RAD52, DCTN2, WNK1, KIF5A, PIP4K2C, NINJ2, DTX3 
## PC_ 3 
## Positive:  IFI27L2, KIAA0196, SQLE, NSMCE2, DICER1, MTSS1, DDX24, TRIB1, NDUFB9, DICER1-AS1 
##     FAM84B, TATDN1, SNHG10, RNF139, UNC79, GLRX5, TRMT12, MYC, FAM91A1, UBR7 
##     C14orf132, FAM49B, WDYHV1, ATG2B, ZHX1, ASAP1, C14orf142, C8orf76, GSKIP, EFR3A 
## Negative:  TSTD2, NCBP1, XPA, C9orf156, ANP32B, NANS, TRIM14, TBC1D2, TGFBR1, ALG2 
##     SEC61B, NR4A3, STX17, ERP44, INVS, TEX10, MSANTD3, MSANTD3-TMEFF1, LPPR1, MRPL50 
##     COMMD1, CCT4, B3GNT2, FAM161A, EHBP1, WDPCP, TIA1, C2orf42, XPO1, ZNF189 
## PC_ 4 
## Positive:  ACSS2, GSS, GGT7, TRPC4AP, TP53INP2, NCOA6, EDEM2, PIGU, EIF6, CEP250 
##     MAP1LC3A, ERGIC3, CPNE1, DYNLRB1, RBM12, NFS1, ITCH, ROMO1, RBM39, PHF20 
##     AHCY, VPS29, SCAND1, FAM216A, LINC00657, EIF2S2, GPN3, EPB41L1, AAR2, ARPC3 
## Negative:  POLG, ABHD2, PEX11A, MFGE8, AEN, AP3S2, DET1, C15orf38-AP3S2, MRPS11, C15orf38 
##     MAN2A2, UNC45A, CRTC3, IDH2, NGRN, MRPL46, HDDC3, CIB1, VPS33B, NTRK3 
##     CHD2, RGMA, KLHL25, AKAP13, IGF1R, ZNF592, SEC11A, NMB, LRRC28, WDR73 
## PC_ 5 
## Positive:  SGTB, NLN, TRAPPC13, TRIM23, PPWD1, CWC27, RNF180, IPO11, DIMT1, KIF2A 
##     ZSWIM6, SMIM15, ADAMTS1, NDUFAF2, APP, N6AMT1, LTN1, GABPA, ATP5J, RWDD2B 
##     ERCC8, JAM2, USP16, PLK2, CCT8, MRPL39, BACH1, TIAM1, NCAM2, GPBP1 
## Negative:  MFNG, CDC42EP1, GGA1, PDXP, LGALS1, H1F0, GCAT, ANKRD54, EIF3L, POLR2F 
##     PLA2G6, MAFF, TMEM184B, CSNK1E, DDX17, CBY1, TOMM22, JOSD1, GTPBP1, SUN2 
##     DNAL4, NPTXR, PDGFB, RPL3, SYNGR1, TAB1, ATF4, RPS19BP1, TNRC6B, ADSL
## Computing nearest neighbor graph
## Computing SNN
## Warning: Data is of class matrix. Coercing to dgCMatrix.
## Finding variable features for layer counts
## Centering and scaling data matrix
## PC_ 1 
## Positive:  BANP, KLHDC4, MAP1LC3B, IRF8, COX4I1, EMC8, CRISPLD2, USP10, COTL1, SUDS3 
##     TAOK3, PEBP1, VSIG10, WSB2, TAF1C, RFC5, FBXO21, JRK, FBXW8, CASP2 
##     GSTK1, FAM131B, MTRNR2L6, RNFT2, ZFYVE27, ARC, CRTAC1, AVPI1, ZYX, R3HCC1L 
## Negative:  SCFD2, FIP1L1, DANCR, SGCB, DCUN1D4, OCIAD1, CHIC2, FRYL, PDGFRA, NFXL1 
##     SRD5A3, COMMD8, GNPDA2, TMEM165, GUF1, CLOCK, ATP8A1, EXOC1, AASDH, PPAT 
##     SLC30A9, PAICS, SRP72, NOA1, POLR2B, LPHN3, UBA6, YTHDC1, TMEM33, UTP3 
## PC_ 2 
## Positive:  PLD2, PSMB6, SLC25A11, CXCL16, RNF167, ARRB2, PELP1, MED11, PFN1, MYBBP1A 
##     XAF1, SPAG7, UBE2G1, C17orf100, TXNDC17, RNASEK, WSCD1, ANKFY1, CAMTA2, MIS12 
##     C17orf49, ZFP3, DERL2, RPAIN, ZNF232, CYB5D2, ACADVL, C1QBP, ZNF594, NUP88 
## Negative:  COG1, FAM104A, CD300A, SSTR2, C17orf80, BTBD17, SLC39A11, SOX9, CDC42EP4, SLC9A3R1 
##     KCNJ16, TTYH2, RPL38, ABCA8, PRKAR1A, NAT9, AMZ2, LINC00674, KPNA2, TMEM104 
##     C17orf58, BPTF, FDXR, NOL11, PSMD12, HID1, HELZ, CDR2L, CACNG4, PRKCA 
## PC_ 3 
## Positive:  APLP2, NFRKB, ZBTB44, SNX19, NTM, IGSF9B, JAM3, NCAPD3, VPS26B, THYN1 
##     ACAD8, B3GAT1, SYNJ2BP, MED6, PCNX, ZFYVE1, RBM25, PSEN1, NUMB, ACOT2 
##     PNMA1, EML1, CYP46A1, ELMSAN1, EVL, YY1, CCNK, PTGR2, FAM161B, COQ6 
## Negative:  FAM21C, AGAP4, PARG, ZNF485, ALOX5, VSTM4, CXCL12, ZNF32, ZNF22, ZNF239 
##     NCOA4, RASSF4, ARHGAP22, BMS1P1, HNRNPF, GLUD1P7, MAPK8, FAM21B, BMS1P2, BMS1P6 
##     AGAP9, ZNF488, BMS1P5, CSGALNACT2, TIMM23, BMS1, ZNF33B, AGAP6, ZNF37BP, HSD17B7P2 
## PC_ 4 
## Positive:  GEMIN2, TRAPPC6B, PNN, CTAGE5, SEC23A, KLHL28, LINC00639, FAM179B, TMX1, TRIM9 
##     NIN, PYGL, PRPF39, MBIP, ATL1, MAP4K5, FKBP3, ATP5S, MDGA2, RPS29 
##     MIS18BP1, BRMS1L, RPL36AL, L2HGDH, MGAT2, DNAAF2, ARF6, NEMF, KLHDC1, KLHDC2 
## Negative:  TBXAS1, SLC37A3, LUC7L2, HIPK2, C7orf55, MKRN1, UBN2, NDUFB2, ZC3HAV1, BRAF 
##     TRIM24, AHSA2, USP34, CREB3L2, C2orf74, XPO1, MRPS33, PEX13, FAM161A, DGKI 
##     REL, CCT4, AGK, TMED8, PTN, VIPAS39, AHSA1, COMMD1, GSTZ1, SPTLC2 
## PC_ 5 
## Positive:  SYNJ2BP, MED6, PCNX, ZFYVE1, RBM25, PSEN1, NUMB, ACOT2, PNMA1, ELMSAN1 
##     PTGR2, ZNF410, FAM161B, COQ6, ALDH6A1, LIN52, UBIAD1, MTOR, EXOSC10, SRM 
##     TARDBP, DFFA, PGD, KIF1B, ABCD4, UBE4B, NMNAT1, CNTLN, PSIP1, SNAPC3 
## Negative:  NUP88, RPAIN, RABEP1, ZNF594, C1QBP, ZNF232, DERL2, ZFP3, CAMTA2, MIS12 
##     SPAG7, WSCD1, PFN1, TXNDC17, RNF167, SLC25A11, PLD2, C17orf100, PSMB6, CXCL16 
##     XAF1, MED11, ARRB2, RNASEK, PELP1, MYBBP1A, UBE2G1, C17orf49, MARCH5, EXOC6
## Computing nearest neighbor graph
## Computing SNN
## Warning: Data is of class matrix. Coercing to dgCMatrix.
## Finding variable features for layer counts
## Centering and scaling data matrix
## PC_ 1 
## Positive:  CHRNB1, NLGN2, ZBTB4, TMEM256, POLR2A, GPS2, EIF4A1, EIF5A, CTDNEP1, GABARAP 
##     PHF23, DVL2, ACADVL, C17orf49, RNASEK, XAF1, ZNF594, RABEP1, C17orf100, ZNF232 
##     NUP88, TXNDC17, RPAIN, DERL2, ZFP3, MIS12, C1QBP, WSCD1, CAMTA2, AMZ1 
## Negative:  MRPL42, UBE2N, CRADD, EEA1, CCDC41, ACTR6, SCYL2, BTG1, TMCC3, ANO4 
##     ATP2B1, NDUFA12, ARL1, NR2C1, GNPTAB, POC1B, CCDC53, NUP37, DUSP6, ASCL1 
##     NT5DC3, C12orf29, HSP90B1, RSU1, STAM, C12orf73, FAM188A, NSUN6, CCDC59, ARL5B 
## PC_ 2 
## Positive:  PTPN1, ADNP, TMEM189, DPM1, UBE2V1, MOCS3, ATP9A, RNF114, ZFP64, BCAS1 
##     SLC9A8, ZFAS1, ARFGEF2, PFDN4, CSE1L, ZNFX1, STAU1, DDX27, DOK5, CSTF1 
##     RTFDC1, BMP7, RAE1, MTRNR2L3, VAPB, STX16, NPEPL1, ATP5J2, ZNF789, ZNF394 
## Negative:  ING2, RWDD4, CDKN2AIP, AGA, TRAPPC11, SPCS3, STOX2, GPM6A, SH3D19, PET112 
##     RPS3A, ARFIP1, TRIM2, FBXW7, KIAA0922, DCLK2, GLRA3, TLR2, PRMT10, ZKSCAN8 
##     PLRG1, IRF2, TMEM184C, CTSO, SLC10A7, CEP44, LSM6, PDGFC, ZSCAN9, FBXO8 
## PC_ 3 
## Positive:  ATP6V1H, RB1CC1, TCEA1, PCMTD1, LYPLA1, UBE2V2, MRPL15, TMEM68, TGS1, ERLIN2 
##     PROSC, DUSP26, BRF2, RNF122, RPS20, EIF4EBP1, MAK16, ASH2L, TTI2, FUT10 
##     LSM1, CHCHD7, PPP2CB, BAG4, IMPAD1, DDHD2, ZCCHC8, UBXN8, CLIP1, VPS33A 
## Negative:  TBK1, GNS, XPOT, LEMD3, C12orf66, LLPH, TMBIM4, CAND1, DYRK2, SRGAP1 
##     MDM1, RAP1B, TMEM5, NUP107, NMI, RND3, RIF1, SLC35E3, PPM1H, MMADHC 
##     KIF5C, ARL5A, EPC2, CACNB4, STAM2, MDM2, MON2, PAPOLA, VRK1, GSKIP 
## PC_ 4 
## Positive:  TRPC4AP, GSS, EDEM2, EIF6, ACSS2, CEP250, CPNE1, ERGIC3, GGT7, RBM12 
##     NFS1, TP53INP2, ROMO1, NCOA6, RBM39, PIGU, PHF20, MAP1LC3A, DYNLRB1, SCAND1 
##     ITCH, LINC00657, AHCY, EPB41L1, AAR2, EIF2S2, DLGAP4, RALY, C20orf24, PXMP4 
## Negative:  GCC2, ST6GAL2, LIMS1, UXS1, RANBP2, NCK2, SEPT10, C2orf49, RGPD5, GPR45 
##     LINC00116, MRPS9, MERTK, MAP4K4, RNF149, ZC3H8, RPL31, PDCL3, TTL, CHST10 
##     AFF3, REV1, EIF5B, TXNDC9, MRPL30, MITD1, MGAT4A, LIPT1, NR1H3, ACP2 
## PC_ 5 
## Positive:  GOT1, SLC25A28, CUTC, COX15, DNMBP, HPS1, ERLIN1, CHUK, CWF19L1, BLOC1S2 
##     SFXN2, WBP1L, SCD, ARL3, R3HCC1L, C10orf32, TRIM8, LINC00263, AS3MT, NT5C2 
##     DCTPP1, LDB1, SEC31B, ACTR1A, PPRC1, NOLC1, GBF1, INA, FBXL15, TMEM180 
## Negative:  MED28, DCAF16, LCORL, PACRGL, LAP3, DHX15, ANAPC4, QDPR, RBPJ, TBC1D19 
##     TAPT1-AS1, ARAP2, RELL1, FAM200B, PGM2, FBXL5, KLF3, TLR1, CC2D2A, TMEM156 
##     RAB28, KLHL5, WDR1, RFC1, RPL9, ACOX3, LIAS, SH3TC1, UGDH, UGDH-AS1
## Computing nearest neighbor graph
## Computing SNN

Basic ouput from running inferCNV.

Additional Information

Online Documentation

For additional explanations on files, usage, and a tutorial please visit the wiki.

TrinityCTAT

This tool is a part of the TrinityCTAT toolkit focused on leveraging the use of RNA-Seq to better understand cancer transcriptomes. To find out more please visit TrinityCTAT

Session info

## R version 4.4.2 (2024-10-31)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.1 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: Etc/UTC
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] infercnv_1.23.0  BiocStyle_2.35.0
## 
## loaded via a namespace (and not attached):
##   [1] RcppAnnoy_0.0.22            splines_4.4.2              
##   [3] later_1.4.1                 bitops_1.0-9               
##   [5] tibble_3.2.1                polyclip_1.10-7            
##   [7] fastDummies_1.7.4           lifecycle_1.0.4            
##   [9] fastcluster_1.2.6           edgeR_4.5.1                
##  [11] doParallel_1.0.17           globals_0.16.3             
##  [13] lattice_0.22-6              MASS_7.3-61                
##  [15] magrittr_2.0.3              limma_3.63.2               
##  [17] plotly_4.10.4               sass_0.4.9                 
##  [19] rmarkdown_2.29              jquerylib_0.1.4            
##  [21] yaml_2.3.10                 httpuv_1.6.15              
##  [23] Seurat_5.1.0                sctransform_0.4.1          
##  [25] spam_2.11-0                 sp_2.1-4                   
##  [27] spatstat.sparse_3.1-0       reticulate_1.40.0          
##  [29] cowplot_1.1.3               pbapply_1.7-2              
##  [31] buildtools_1.0.0            RColorBrewer_1.1-3         
##  [33] multcomp_1.4-26             abind_1.4-8                
##  [35] Rtsne_0.17                  GenomicRanges_1.59.1       
##  [37] purrr_1.0.2                 BiocGenerics_0.53.3        
##  [39] TH.data_1.1-2               sandwich_3.1-1             
##  [41] GenomeInfoDbData_1.2.13     IRanges_2.41.2             
##  [43] S4Vectors_0.45.2            ggrepel_0.9.6              
##  [45] irlba_2.3.5.1               listenv_0.9.1              
##  [47] spatstat.utils_3.1-1        maketools_1.3.1            
##  [49] goftest_1.2-3               RSpectra_0.16-2            
##  [51] spatstat.random_3.3-2       fitdistrplus_1.2-1         
##  [53] parallelly_1.41.0           leiden_0.4.3.1             
##  [55] codetools_0.2-20            coin_1.4-3                 
##  [57] DelayedArray_0.33.3         tidyselect_1.2.1           
##  [59] futile.logger_1.4.3         UCSC.utils_1.3.0           
##  [61] farver_2.1.2                rjags_4-16                 
##  [63] matrixStats_1.4.1           stats4_4.4.2               
##  [65] spatstat.explore_3.3-3      jsonlite_1.8.9             
##  [67] progressr_0.15.1            ggridges_0.5.6             
##  [69] survival_3.8-3              iterators_1.0.14           
##  [71] foreach_1.5.2               tools_4.4.2                
##  [73] ica_1.0-3                   Rcpp_1.0.13-1              
##  [75] glue_1.8.0                  gridExtra_2.3              
##  [77] SparseArray_1.7.2           xfun_0.49                  
##  [79] MatrixGenerics_1.19.0       GenomeInfoDb_1.43.2        
##  [81] dplyr_1.1.4                 formatR_1.14               
##  [83] BiocManager_1.30.25         fastmap_1.2.0              
##  [85] caTools_1.18.3              digest_0.6.37              
##  [87] parallelDist_0.2.6          R6_2.5.1                   
##  [89] mime_0.12                   colorspace_2.1-1           
##  [91] scattermore_1.2             gtools_3.9.5               
##  [93] tensor_1.5                  spatstat.data_3.1-4        
##  [95] tidyr_1.3.1                 generics_0.1.3             
##  [97] data.table_1.16.4           httr_1.4.7                 
##  [99] htmlwidgets_1.6.4           S4Arrays_1.7.1             
## [101] uwot_0.2.2                  pkgconfig_2.0.3            
## [103] gtable_0.3.6                modeltools_0.2-23          
## [105] lmtest_0.9-40               SingleCellExperiment_1.29.1
## [107] XVector_0.47.1              sys_3.4.3                  
## [109] htmltools_0.5.8.1           dotCall64_1.2              
## [111] SeuratObject_5.0.2          scales_1.3.0               
## [113] Biobase_2.67.0              png_0.1-8                  
## [115] phyclust_0.1-34             spatstat.univar_3.1-1      
## [117] knitr_1.49                  lambda.r_1.2.4             
## [119] reshape2_1.4.4              coda_0.19-4.1              
## [121] nlme_3.1-166                cachem_1.1.0               
## [123] zoo_1.8-12                  stringr_1.5.1              
## [125] KernSmooth_2.23-24          parallel_4.4.2             
## [127] miniUI_0.1.1.1              libcoin_1.0-10             
## [129] pillar_1.10.0               grid_4.4.2                 
## [131] vctrs_0.6.5                 gplots_3.2.0               
## [133] RANN_2.6.2                  promises_1.3.2             
## [135] xtable_1.8-4                cluster_2.1.8              
## [137] evaluate_1.0.1              locfit_1.5-9.10            
## [139] mvtnorm_1.3-2               cli_3.6.3                  
## [141] compiler_4.4.2              futile.options_1.0.1       
## [143] rlang_1.1.4                 crayon_1.5.3               
## [145] future.apply_1.11.3         argparse_2.2.5             
## [147] plyr_1.8.9                  stringi_1.8.4              
## [149] viridisLite_0.4.2           deldir_2.0-4               
## [151] munsell_0.5.1               lazyeval_0.2.2             
## [153] spatstat.geom_3.3-4         Matrix_1.7-1               
## [155] RcppHNSW_0.6.0              patchwork_1.3.0            
## [157] future_1.34.0               ggplot2_3.5.1              
## [159] statmod_1.5.0               shiny_1.10.0               
## [161] SummarizedExperiment_1.37.0 ROCR_1.0-11                
## [163] igraph_2.1.2                RcppParallel_5.1.9         
## [165] bslib_0.8.0                 ape_5.8-1