Schematic overview of the cellular and molecular mechanisms involved in the cancer progression, including the proposed cellular and molecular mechanisms in cancer cells trajectory. AT1: alveolar type 1 cells; AT2: alveolar type 2 cells; AAH: atypical adenomatous hyperplasia; AIS: adenocarcinoma in situ; MIA: minimally invasive adenocarcinoma; IA: invasive adenocarcinoma; EMT: epithelial-mesenchymal transition

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Center for Computational Systems Medicine
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Tissue samples summary

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Annotation details for different cell compartments

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Cell type statistics by disease state

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Cell type dynamics in malignant transformation

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Cell lineage trajectory inference

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TF regulatory network analysis

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Cell-cell interaction analysis

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Stemness, Senescence, Metaplasia and NeoTCR signature analysis

Tissue: Cervix

Tissue samples summary

check button Cell type statistics by tissue samples.
EpitheliaImmuneStromal
Bar plot representation of the fraction of all Epithelial cells in each sample composed of each cell type for the integrated scRNA-seq datasets of Breast tissues. Each row represents a single sample, with each color representing a different cell type present in the sample.Bar plot representation of the fraction of all Immune cells in each sample composed of each cell type for the integrated scRNA-seq datasets of Breast tissues. Each row represents a single sample, with each color representing a different cell type present in the sample.Bar plot representation of the fraction of all Stromal cells in each sample composed of each cell type for the integrated scRNA-seq datasets of Breast tissues. Each row represents a single sample, with each color representing a different cell type present in the sample.
∗Bar plot representation of the fraction of all Epithelial, Immune and Stromal cells in each sample composed of each cell type for the integrated scRNA-seq datasets of Cervix tissue. Each row represents a single sample, with each color representing a different cell type present in the sample.

check button Tissue summary table.
TissueDisease StateReplicatesEpithelia UMAPPMIDSourcePlatform
CervixCCCA_HPV_1Projection

36967539

GSE208653

10X Genomics
CervixCCCA_HPV_2Projection

36967539

GSE208653

10X Genomics
CervixCCCA_HPV_3Projection

36967539

GSE208653

10X Genomics
CervixHSIL_HPVHSIL_HPV_1Projection

36967539

GSE208653

10X Genomics
CervixHSIL_HPVHSIL_HPV_2Projection

36967539

GSE208653

10X Genomics
CervixN_HPVN_HPV_1Projection

36967539

GSE208653

10X Genomics
CervixN_HPVN_HPV_2Projection

36967539

GSE208653

10X Genomics
CervixCCCCI_1Projection

NA

SCP1950

10X Genomics
CervixCCCCI_2Projection

NA

SCP1950

10X Genomics
CervixCCCCI_3Projection

NA

SCP1950

10X Genomics
CervixCCCCI_4Projection

NA

SCP1950

10X Genomics
CervixCCCCII_1Projection

NA

SCP1950

10X Genomics
CervixCCCCII_2Projection

NA

SCP1950

10X Genomics
CervixCCCCII_3Projection

NA

SCP1950

10X Genomics
CervixCCTumorProjection

33996252

GSE168652

10X Genomics
CervixCCsample1Projection

36357663

E-MTAB-11948

10X Genomics
CervixCCsample2Projection

36357663

E-MTAB-11948

10X Genomics
CervixCCsample3Projection

36357663

E-MTAB-11948

10X Genomics
CervixADJsample4Projection

36357663

E-MTAB-11948

10X Genomics
CervixADJsample5Projection

36357663

E-MTAB-11948

10X Genomics
∗Projection of epithelial scRNA-seq cells from Cervix diseased tissue samples into the manifold of normal tissue epithelial cells. Projected cells are colored by nearest normal cells in the projection and normal epithelial cells are colored gray.
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Annotation details for different cell compartments

check button Single-cell atlas of expresion.
UMAP representations and annotations of Epithelial cells in the integrated scRNA-seq data of the selected tissue.UMAP representations and annotations of Immune cells in the integrated scRNA-seq data of the selected tissue.UMAP representations and annotations of Stromal cells in the integrated scRNA-seq data of the selected tissue.
∗UMAP representations and annotations of Epithelial, Immune, Stromal cells in the integrated scRNA-seq data of Cervix tissue. Colors represent cell types of each compartment.

check button Cell markers.
TissueMajor Cell TypeMinor Cell TypeFull NameMarkers
CervixEpiSTMStem-like cellsALDH3A1,ALDH1A1,BMI1,SFRP1,ITGB1,LGR5,SOX2,POU5F1,NANOG,CD44,TP63,ABCG2,PROM1,ALCAM
CervixEpiBASBasal cellsKRT5,KRT14,KRT6A,KRT15,TP63,ITGA6,ITGB4
CervixEpiMESCervical Mesothelial cellsWT1,CALB1,VIM,CDH1,MSLN,BAP1
CervixEpiCOLColumnar epithelial cellsSOX17,CLDN15,MUC17,MUC16,MUC5B,MUC6,PAX8
CervixEpiKERKeratinocytesKRT5,KRT13,KRT14,KRT4,KRT18,KRT17,IVL,LOR,SPRR3
CervixEpiTRANSTransit-amplifying cellsUPK1A,DSP,SERPINB3
CervixImmNEUTNeutriphilsCEACAM3,FCGR3B,CXCR2
CervixImmMASTMast cellsTPSAB1,CPA3,HDC,CTSG,TPSB2,CMA1,MS4A2
CervixImmDCDendritic cellsHLA-DQA1,HLA-DQB1,CLEC10A,CLEC9A,FCER1A,CST3,CD1C
CervixImmNKNatural killer cellsKLRF1,SH2D1B,NCAM1,FCGR3A,GNLY,NKG7,GZMH,FGFBP2,CX3CR1,NCR1,NCR3,B3GAT1
CervixImmMONMonocytesCD14,CLEC9A,FCGR1A,LILRB2,CD209,CD1E,FCN1,VCAN
CervixImmM1MACM1 macrophagesFOLR2,FABP3,PLA2G2D,ITGAM,ITGAX,CSF1R,CD68,CD163,THBD
CervixImmINMONInflamotory monocytesCD14,CLEC9A,FCGR1A,LILRB2,CD209,CD1E,FCN1,VCAN,S100A8,S100A9
CervixImmM2MACM2 macrophagesCSF1R,CSF3R,MRC1,IL10,CCL18,VSIG4,CHI3L1
CervixImmBNNaive B cellsCD19,IGHD,IGLL1,CD27,CD38
CervixImmBMEMMemory B cellsPAX5,MS4A1,CD19,IGLL5,VPREB3,CD79A,CD79B,IGKC,CD74,HLA-DRA,CD37,CD22
CervixImmGCGerminal center B cellsSERPINA9,HRK,HTR3A,BCL6,CD180,FCRLA
CervixImmPLAPlasma cellsSSR4,IGLL5,IGLL1,AMPD1,IGHA1,IGHA2,JCHAIN,CD38,TNFRSF17,SDC1,IGHG1,MZB1
CervixImmGDTGamma-delta T cellsTRDC,TRGC1,TRGC2,NKG7,TIGIT
CervixImmCD8TEXExhausted CD8+ T cellsPDCD1,LAG3,CD101,CD38,CXCR6,TIGIT
CervixImmCD4TNNaive CD4+ T cellsIL7R,SELL,CCR7,S100A4,TCF7
CervixImmTFHT follicular helperCXCR5,BCL6,ICA1,TOX,TOX2,IL6ST,MAGEH1,BTLA,ICOS,PDCD1,CD200
CervixImmTREGRegulatory T cellsBATF,TNFRSF4,FOXP3,CTLA4,LAIR2,IL2RA
CervixImmMAITMucosal-associated invariant T cellsSLC4A10,DPP4,KLRB1,ZBTB16,NCR3,RORC,RORA
CervixImmCD8TEXPProgenitor exhausted CD8+ T cellsPDCD1,IL7R,GPR183,NR4A3,REL,TCF7
CervixImmCD8TEXINTIntermediate exhausted CD8+ T cellsPDCD1,LAG3,CD101,CD38,CXCR6,TIGIT
CervixImmCD8TEREXTerminally exhausted CD8+ T cellsTOX,GZMB,ENTPD1,ITGAE,HAVCR2,CXCL13,PDCD1,LAYN,TOX,IFNG,GZMB,MIR155HG,TNFRSF9,ITGAE
CervixImmCD8TCMCentral memory CD8+ T cellsCCR7,SELL,IL7R,CD27,CD28,PRF1,GZMA,CCL5,GPR183,S1PR1
CervixImmCD8TRMCD8+ tissue resident memory T cellsCD6,XCL1,XCL2,MYADM,CAPG,RORA,NR4A1,NR4A2,NR4A3,CD69,ITGAE
CervixImmCD8TEFFEffector CD8+ T cellsCX3CR1,FCGR3A,FGFBP2,PRF1,GZMH,TBX21,EOMES,S1PR1
CervixStrENDEndothelial cellsPECAM1,PLVAP,VWF,CLDN5,FLT1,RAMP2,FAM110D,INHBB,NPR1,NOVA2,GPIHBP1,SOX17
CervixStrLYMENDLymphatic endothelial cellsPROX1,LYVE1,PDPN,PROCR,FLT4
CervixStrFIBFibroblastsBMP7,MAP3K2,COL6A1,CD36,CD44,CBLN2,SPOCK1,ACSS3,FN1,COL3A1,BGN,DCN,POSTN,C1R,MMP2,FGF7,MME,CD47
CervixStrSMCSmooth muscle cellsACTA2,CNN1,MYH11,TAGLN,CALD1,TAGLN2
CervixStrMYOFIBMyofibroblastsSYT10,SOSTDC1,DES,TAGLN,MYH11,TPM4
CervixStrPERIPericytesPDGFRA,CSPG4,RGS5,MCAM,COX4I2,KCNJ8,HIGD1B,NOTCH3,HEYL,FAM162B
CervixStrSTMLStem-like cellsWNT5B,WNT2B,RSPO3,LGR5,FGF10,DLL1
CervixStrADIPOAdipocytesPPARG,FABP4,ADIPOQ,LEP,CD36,PLIN1
CervixStrPVAPost capillary venulesSELP,ZNF385D,FAM155A,GALNT15,MADCAM1,CORT
CervixStrMVAMicrovascular cellsPLVAP,CD36,DYSF,NRP1,SH3BP5,EXOC3L2,FABP5,VWA1,BAALC,PRSS23,RAPGEF4,APLN,HTRA1
CervixStrECMExtracellular matrixFBLN1,PCOLCE2,MFAP5
CervixStrBSMBasement membraneCOL4A5,COL4A6
CervixStrINCAFIntermediate cancer-associated fibroblastsPDGFRA,POSTN,ID1,ID3
CervixStrICAFInflammatory cancer-associated fibroblastsTWIST1,WNT2,FAP,CXCL1,CXCL2,CYR61,IL1B,IL6,HGF
CervixStrCAFCancer-associated fibroblastsTWIST1,WNT2,FAP,CXCL1,CXCL2,CYR61

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Cell type statistics by disease state

Stacked bar graph representation of the fraction of each epithelial cell type derived from samples with different Disease States in the integrated dataset of the selected tissue. Cells from each Disease State sample have a different color.Stacked bar graph representation of the fraction of each immune cell type derived from samples with different Disease States in the integrated dataset of the selected tissue. Cells from each Disease State sample have a different color.Stacked bar graph representation of the fraction of each stromal cell type derived from samples with different Disease States in the integrated dataset of the selected tissue. Cells from each Disease State sample have a different color.
∗Stacked bar graph representation of the fraction of each epithelial cell type derived from samples with different Disease States in the integrated dataset of Cervix tissue. Cells from each Disease State sample have a different color.

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Cell type dynamics in malignant transformation

Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in the selected tissue. Samples are colored based on if they are derived from different Disease States.
∗Fraction of cell type in each scRNA-seq sample plotted against position of the sample in the malignancy continuum for all cell types in Cervix tissue. Samples are colored based on if they are derived from different Disease States. Cell fractions are computed by dividing the number of cells of a given cell type by the total number of cells in the compartment (epithelial versus immune versus stromal).
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Cell lineage trajectory inference

Disease StateEpitheliaImmuneStromal
HealthyTrajectory analysis of cells of epithelial compartment in Healthy-derived samples of Cervix tissue by using scvelo package in Python.Trajectory analysis of cells of immune compartment in Healthy-derived samples of Cervix tissue by using scvelo package in Python.Trajectory analysis of cells of stromal compartment in Healthy-derived samples of Cervix tissue by using scvelo package in Python.
PrecancerTrajectory analysis of cells of epithelial compartment in Precancer-derived samples of Cervix tissue by using scvelo package in Python.Trajectory analysis of cells of immune compartment in Precancer-derived samples of Cervix tissue by using scvelo package in Python.Trajectory analysis of cells of stromal compartment in Precancer-derived samples of Cervix tissue by using scvelo package in Python.
CCTrajectory analysis of cells of epithelial compartment in CC-derived samples of Cervix tissue by using scvelo package in Python.Trajectory analysis of cells of immune compartment in CC-derived samples of Cervix tissue by using scvelo package in Python.Trajectory analysis of cells of stromal compartment in CC-derived samples of Cervix tissue by using scvelo package in Python.
∗RNA velocity maps for epithelial, immune and stromal compartments of Cervix tissue with different disease states.

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TF regulatory network analysis

Disease StateEpitheliaImmuneStromal
HealthyHeatmap representation of significantly different TFs among all cell types of epithelial compartment in Healthy-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of immune compartment in Healthy-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of stromal compartment in Healthy-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.
TF target networkTF target networkTF target network
ADJHeatmap representation of significantly different TFs among all cell types of epithelial compartment in ADJ-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of immune compartment in ADJ-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of stromal compartment in ADJ-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.
TF target networkTF target networkTF target network
PrecancerHeatmap representation of significantly different TFs among all cell types of epithelial compartment in Precancer-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of immune compartment in Precancer-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of stromal compartment in Precancer-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.
TF target networkTF target networkTF target network
CCHeatmap representation of significantly different TFs among all cell types of epithelial compartment in CC-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of immune compartment in CC-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.Heatmap representation of significantly different TFs among all cell types of stromal compartment in CC-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python.
TF target networkTF target networkTF target network
∗Heatmap: Heatmap representation of significantly different TFs among all cell types of epithelial compartment in Healthy-derived samples of Cervix tissue by comparing their average AUC by using pySCENIC in Python. Regulon specific score for each cell type is colored.
∗Network: TF target network created from Healthy-derived samples of Cervix tissue using Top 50 predicted target genes of each regulon. Edge lengths are the inferred TF-target weightings.

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Cell-cell interaction analysis

Disease StateCell TypeCircleSourceTarget
HealthyBASThe cell-cell communications between each two interacting cell types in Healthy-derived samples of the selected tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in Healthy-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in Healthy-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.
BNThe cell-cell communications between each two interacting cell types in Healthy-derived samples of the selected tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in Healthy-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in Healthy-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.
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Disease StateCell TypeCircleSourceTarget
ADJBASThe cell-cell communications between each two interacting cell types in ADJ-derived samples of the selected tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs. Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in ADJ-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in ADJ-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.
BNThe cell-cell communications between each two interacting cell types in ADJ-derived samples of the selected tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs. Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in ADJ-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in ADJ-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.
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Disease StateCell TypeCircleSourceTarget
PrecancerBASThe cell-cell communications between each two interacting cell types in Precancer-derived samples of the selected tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs. Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in Precancer-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in Precancer-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.
BNThe cell-cell communications between each two interacting cell types in Precancer-derived samples of the selected tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs. Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in Precancer-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in Precancer-derived samples of the selected tissue. Each row represents the significant ligand and receptor gene pairs.
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Disease StateCell TypeCircleSourceTarget
CCBASThe cell-cell communications between each two interacting cell types in CC-derived samples of Cervix tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs. Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in CC-derived samples of Cervix tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in CC-derived samples of Cervix tissue. Each row represents the significant ligand and receptor gene pairs.
BMEMThe cell-cell communications between each two interacting cell types in CC-derived samples of Cervix tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs. Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source cell population in CC-derived samples of Cervix tissue. Each row represents the significant ligand and receptor gene pairs.Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its target cell population in CC-derived samples of Cervix tissue. Each row represents the significant ligand and receptor gene pairs.
∗The cell-cell communications between each two interacting cell types in different states-derived samples of Cervix tissue. Different colors in the circle plot represent different cell groups and the edge width is proportional to the indicated number of ligand-receptor pairs.
∗Bubble plot of proportion to the communication probability in significant signaling pathways between this cell type and its source and target cell population. Each row represents the significant ligand and receptor gene pairs.
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Stemness, Senescence, Metaplasia and NeoTCR signature analysis

check button Developmental potential inference using CytoTRACE.
1_developmental_potential_in_Healthy.png shows the analysis results of stemness, senescence, and metaplasia signatures2_developmental_potential_in_Precancer.png shows the analysis results of stemness, senescence, and metaplasia signatures3_developmental_potential_in_CC.png shows the analysis results of stemness, senescence, and metaplasia signatures
∗Ridge plots of CytoTRACE score distributions for epithelial cells.

check button Cellular senescence signature (for three compartments).
Disease StateEpitheliaImmuneStromal
HealthyComparisons for degree of cellular senescence of epithelial compartment in Healthy-derived samples of Cervix tissue.Comparisons for degree of cellular senescence of immune compartment in Healthy-derived samples of Cervix tissue.Comparisons for degree of cellular senescence of stromal compartment in Healthy-derived samples of Cervix tissue.
PrecancerComparisons for degree of cellular senescence of epithelial compartment in Precancer-derived samples of Cervix tissue.Comparisons for degree of cellular senescence of immune compartment in Precancer-derived samples of Cervix tissue.Comparisons for degree of cellular senescence of stromal compartment in Precancer-derived samples of Cervix tissue.
CCComparisons for degree of cellular senescence of epithelial compartment in CC-derived samples of Cervix tissue.Comparisons for degree of cellular senescence of immune compartment in CC-derived samples of Cervix tissue.Comparisons for degree of cellular senescence of stromal compartment in CC-derived samples of Cervix tissue.
∗Comparisons for degree of cellular senescence among epithelial, immune and stromal cell populations of Cervix tissue with different disease states.

check button Metaplasia and damage response signature (for epithelial cells).
HealthyPrecancerCC
Comparisons of Metaplasia-associated damage scores among epithelial cell subpopulations.Comparisons of Metaplasia-associated damage scores among epithelial cell subpopulations.Comparisons of Metaplasia-associated damage scores among epithelial cell subpopulations.
∗Comparisons of Metaplasia-associated damage scores among epithelial cell subpopulations.

check button Neoantigen-specific TCR clonotypes (NeoTCR) signature.
Comparisons of CD4+ and CD8+ NeoTCR signature scores among different disease states.Comparisons of CD4+ and CD8+ NeoTCR signature scores among different disease states.
∗Comparisons of CD4+ and CD8+ NeoTCR signature scores among different disease states.