inferCNV uses the R packages ape, BiocGenerics, binhf, caTools, coda, coin, dplyr, doparallel, edgeR, fastcluster, fitdistrplus, foreach, futile.logger, future, gplots, ggplot2, HiddenMarkov, leiden, phyclust, RANN, reshape, rjags, RColorBrewer, SingleCellExperiment, SummarizedExperiment, tidyr and imports functions from the archived GMD.
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:
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 [2024-10-30 08:34:43] Parsing matrix: ../inst/extdata/oligodendroglioma_expression_downsampled.counts.matrix.gz
## INFO [2024-10-30 08:34:45] Parsing gene order file: ../inst/extdata/gencode_downsampled.EXAMPLE_ONLY_DONT_REUSE.txt
## INFO [2024-10-30 08:34:45] Parsing cell annotations file: ../inst/extdata/oligodendroglioma_annotations_downsampled.txt
## INFO [2024-10-30 08:34:45] ::order_reduce:Start.
## INFO [2024-10-30 08:34:45] .order_reduce(): expr and order match.
## INFO [2024-10-30 08:34:45] ::process_data:order_reduce:Reduction from positional data, new dimensions (r,c) = 10338,184 Total=18322440.6799817 Min=0 Max=34215.
## INFO [2024-10-30 08:34:45] num genes removed taking into account provided gene ordering list: 399 = 3.8595473012188% removed.
## INFO [2024-10-30 08:34:45] -filtering out cells < 100 or > Inf, removing 0 % of cells
## WARN [2024-10-30 08:34:45] 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 [2024-10-30 08:34:45] validating infercnv_obj
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.
For additional explanations on files, usage, and a tutorial please visit the wiki.
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
This methodology was used in:
## R version 4.4.1 (2024-06-14)
## 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_4.4.1
## [3] later_1.3.2 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_4.3.21
## [11] doParallel_1.0.17 globals_0.16.3
## [13] lattice_0.22-6 MASS_7.3-61
## [15] magrittr_2.0.3 limma_3.61.12
## [17] plotly_4.10.4 sass_0.4.9
## [19] rmarkdown_2.28 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_1.39.0
## [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] zlibbioc_1.51.2 Rtsne_0.17
## [37] GenomicRanges_1.57.2 purrr_1.0.2
## [39] BiocGenerics_0.53.0 TH.data_1.1-2
## [41] sandwich_3.1-1 GenomeInfoDbData_1.2.13
## [43] IRanges_2.39.2 S4Vectors_0.43.2
## [45] ggrepel_0.9.6 irlba_2.3.5.1
## [47] listenv_0.9.1 spatstat.utils_3.1-0
## [49] maketools_1.3.1 goftest_1.2-3
## [51] RSpectra_0.16-2 spatstat.random_3.3-2
## [53] fitdistrplus_1.2-1 parallelly_1.38.0
## [55] leiden_0.4.3.1 codetools_0.2-20
## [57] coin_1.4-3 DelayedArray_0.33.1
## [59] tidyselect_1.2.1 futile.logger_1.4.3
## [61] UCSC.utils_1.1.0 farver_2.1.2
## [63] rjags_4-16 matrixStats_1.4.1
## [65] stats4_4.4.1 spatstat.explore_3.3-3
## [67] jsonlite_1.8.9 progressr_0.15.0
## [69] ggridges_0.5.6 survival_3.7-0
## [71] iterators_1.0.14 foreach_1.5.2
## [73] tools_4.4.1 ica_1.0-3
## [75] Rcpp_1.0.13 glue_1.8.0
## [77] gridExtra_2.3 SparseArray_1.5.45
## [79] xfun_0.48 MatrixGenerics_1.17.1
## [81] GenomeInfoDb_1.41.2 dplyr_1.1.4
## [83] formatR_1.14 BiocManager_1.30.25
## [85] fastmap_1.2.0 fansi_1.0.6
## [87] caTools_1.18.3 digest_0.6.37
## [89] parallelDist_0.2.6 R6_2.5.1
## [91] mime_0.12 colorspace_2.1-1
## [93] scattermore_1.2 gtools_3.9.5
## [95] tensor_1.5 spatstat.data_3.1-2
## [97] utf8_1.2.4 tidyr_1.3.1
## [99] generics_0.1.3 data.table_1.16.2
## [101] httr_1.4.7 htmlwidgets_1.6.4
## [103] S4Arrays_1.5.11 uwot_0.2.2
## [105] pkgconfig_2.0.3 gtable_0.3.6
## [107] modeltools_0.2-23 lmtest_0.9-40
## [109] SingleCellExperiment_1.27.2 XVector_0.45.0
## [111] sys_3.4.3 htmltools_0.5.8.1
## [113] dotCall64_1.2 SeuratObject_5.0.2
## [115] scales_1.3.0 Biobase_2.67.0
## [117] png_0.1-8 phyclust_0.1-34
## [119] spatstat.univar_3.0-1 knitr_1.48
## [121] lambda.r_1.2.4 reshape2_1.4.4
## [123] coda_0.19-4.1 nlme_3.1-166
## [125] cachem_1.1.0 zoo_1.8-12
## [127] stringr_1.5.1 KernSmooth_2.23-24
## [129] parallel_4.4.1 miniUI_0.1.1.1
## [131] libcoin_1.0-10 pillar_1.9.0
## [133] grid_4.4.1 vctrs_0.6.5
## [135] gplots_3.2.0 RANN_2.6.2
## [137] promises_1.3.0 xtable_1.8-4
## [139] cluster_2.1.6 evaluate_1.0.1
## [141] locfit_1.5-9.10 mvtnorm_1.3-1
## [143] cli_3.6.3 compiler_4.4.1
## [145] futile.options_1.0.1 rlang_1.1.4
## [147] crayon_1.5.3 future.apply_1.11.3
## [149] argparse_2.2.3 plyr_1.8.9
## [151] stringi_1.8.4 viridisLite_0.4.2
## [153] deldir_2.0-4 munsell_0.5.1
## [155] lazyeval_0.2.2 spatstat.geom_3.3-3
## [157] Matrix_1.7-1 RcppHNSW_0.6.0
## [159] patchwork_1.3.0 future_1.34.0
## [161] ggplot2_3.5.1 statmod_1.5.0
## [163] shiny_1.9.1 highr_0.11
## [165] SummarizedExperiment_1.35.5 ROCR_1.0-11
## [167] igraph_2.1.1 RcppParallel_5.1.9
## [169] bslib_0.8.0 ape_5.8