Overview
This vignette briefly summarizes the public spatial transcriptomic
datasets of infectious diseases and curated gene resources used by
STID.
Public datasets
Table S1 includes eight public mouse spatial transcriptomic datasets covering viral, bacterial, and parasitic infection models.
| Pathogen type | Pathogen | Abbrev. | Disease | Tissue | Reference | Technology | Repository/accession | n |
|---|---|---|---|---|---|---|---|---|
| Virus | Japanese encephalitis virus | JEV | Japanese encephalitis | Brain | Ou et al. (2026) | Stereo-seq | STT0000076 | 12 |
| Virus | Venezuelan equine encephalitis virus | VEEV | Venezuelan equine encephalitis | Brain | Rangel et al. (2024) | 10x Visium | GSE275201 | 2 |
| Virus | Reovirus type 1 Lang | Reo-T1L | Viral myocarditis | Heart | Mantri et al. (2022) | 10x Visium | GSE189636 | 4 |
| Bacterium | Mycobacterium tuberculosis | MTB | Tuberculosis | Lung | Zhao et al. (2025) | Stereo-seq V2 | CRA018250 | 8 |
| Bacterium | Klebsiella pneumoniae | Kp | Klebsiella pneumoniae pneumonia | Lung | Xu et al. (2022) | 10x Visium | GSE190225 | 4 |
| Parasite | Echinococcus multilocularis | Em | Alveolar echinococcosis | Liver | Ou et al. (2025) | Stereo-seq | STT0000072 | 12 |
| Parasite | Plasmodium berghei ANKA | N/A | Malaria | Liver | Hildebrandt et al. (2024) | 10x Visium | GSE268068 | 4 |
| Parasite | Trypanosoma brucei brucei | Tbb | African trypanosomiasis | Brain | Quintana et al. (2022) | 10x Visium | GSE200642 | 3 |
Raw datasets are available from the repositories reported in the original publications and Table S1. Processed datasets and curated gene and gene-set resources are available from Figshare.
Curated genes and gene sets
Table S2 summarizes 12 curated resources. Counts are shown as
Human/Mouse.
| Type | Name | Main use | Count |
|---|---|---|---|
| Gene | Infection_Immunity | Infection and immune response genes | 391/345 |
| Gene | PRR | Pattern recognition receptor genes | 137/128 |
| Gene | Macrophage | Macrophage polarization/function genes | 35/35 |
| Gene set | GO_BP_Detect_viral | GO biological process terms related to viral infection | 9/12 |
| Gene set | GO_BP_Detect_bacterial | GO biological process terms related to bacterial infection | 10/7 |
| Gene set | KEGG_Detect_viral | KEGG viral infection pathways | 21/21 |
| Gene set | KEGG_Detect_bacterial | KEGG bacterial infection pathways | 11/7 |
| Gene set | KEGG_Detect_parasitic | KEGG parasitic infection pathways | 6/6 |
| Gene set | KEGG_Metabolism | KEGG metabolism pathways | 85/85 |
| Gene set | Reactome_Metabolism | Reactome metabolism pathways | 301/253 |
| Gene set | MSigDB_Hallmark | MSigDB hallmark gene sets | 50/50 |
| Gene set | PCD | Programmed cell death gene sets | 18/18 |
STID::Gene_Geneset
#> $Human
#> $Human$Gene
#> $Human$Gene$Human_Infection_Immunity_gene
#> # A tibble: 110 × 17
#> IFN IRF IFI CXCL CXCR CCL CCR TNF CSF IL NFKB Attacin
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 IFNA1 IRF1… IFIT1 CXCL1 CXCR1 CCL1 CCR1 TNF CSF1 IL1R2 NFKB… CAMP
#> 2 IFNAR1 IRF1 IFIT… CXCL… CXCR… CCL2 CCR2 TNFA… CSF1R IL1R… NFKB… DEFA1
#> 3 IFNA2 IRF2… IFIT… CXCL2 CXCR2 CCL3… CCRL2 TNFR… CSF2 IL1R1 NFKB… DEFA1B
#> 4 IFNAR2 IRF2 IFIT… CXCL3 CXCR3 CCL3 CCR3 TNFR… CSF2… IL1F… NFKB… DEFA3
#> 5 IFNAR2-I… IRF2… IFIH1 CXCL5 CXCR4 CCL3… CCR4 TNFA… CSF2… IL1A NFKB… DEFA4
#> 6 IFNA4 IRF2… IFIT2 CXCL6 CXCR5 CCL4 CCR5… TNFA… CSF2… IL1R… NFKB1 DEFA5
#> 7 IFNA5 IRF2… IFIT… CXCL8 CXCR6 CCL4… CCR5 TNFS… CSF2… ILRU… NFKB… DEFA6
#> 8 IFNA6 IRF3 IFIT… CXCL9 NA CCL5 CCR6 TNFR… CSF3R ILDR1 NFKB2 DEFA7P
#> 9 IFNA7 IRF4 IFIT… CXCL… NA CCL7 CCR7 TNFA… CSF3 IL1RN REL DEFA8P
#> 10 IFNA8 IRF5 IFIT… CXCL… NA CCL8 CCR8 TNFR… NA IL1R… RELA DEFA9P
#> # ℹ 100 more rows
#> # ℹ 5 more variables: ATE <chr>, ROS_NO <chr>, Clq <chr>, Acute_Phase <chr>,
#> # Antigen <chr>
#>
#> $Human$Gene$Human_Macrophage_gene
#> # A tibble: 15 × 3
#> M1 M2 Fusion
#> <chr> <chr> <chr>
#> 1 FCGR3A CD163 ADAM9
#> 2 CD86 MRC1 CD44
#> 3 CD14 ARG1 CD81
#> 4 NOS2 CHI3L1 DCSTAMP
#> 5 IL6 RETN OCSTAMP
#> 6 TNF IL10 STAT1
#> 7 IL1B TGFB1 TREM2
#> 8 IL12B PPARG TYROBP
#> 9 CXCL9 KLF4 NA
#> 10 CXCL10 IL4R NA
#> 11 CD80 CCL17 NA
#> 12 HLA-DRA CCL22 NA
#> 13 IRF5 NA NA
#> 14 SOCS3 NA NA
#> 15 FPR2 NA NA
#>
#> $Human$Gene$Human_PRR_gene
#> # A tibble: 38 × 8
#> TLRs TLRs_downstream CASP NLRs CLRs SRs CRs FcRs
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 TLR1 MYD88 CASP1 NAIP MRC1 MSR1 CR1L FCGRT
#> 2 TLR2 TICAM1 CASP1P2 NAIPP1 CLECL1P SCARB1 CR2 FCGR1BP
#> 3 TLR3 TICAM2 CASP1P1 NAIPP2 CLECL1P CD36 ITGAM FCGR1BP
#> 4 TLR4 TICAM2-AS1 CASP2 NAIPP3 CLEC1B SCARB1 ITGAX FCGR1CP
#> 5 CD14 TIRAP CASP3P1 NAIPP4 CLEC1A MARCO FCGR1A FCGR1A
#> 6 TLR5 TRAM1L1 CASP3 NODAL CLEC2L CD163 NA FCGR2A
#> 7 TLR6 TRAM1 CASP4LP NOD1 CLEC2D NA NA FCGR2C
#> 8 TLR7 TRAM2 CASP4LP NOD2 CLEC2B NA NA FCGR2B
#> 9 TLR8-AS1 TRAM2-AS1 CASP4 NLRC3 CLEC2A NA NA FCGR3A
#> 10 TLR8 TRAF1 CASP5 NLRC4 CLEC3B NA NA FCGR3B
#> # ℹ 28 more rows
#>
#>
#> $Human$Geneset
#> $Human$Geneset$GO
#> $Human$Geneset$GO$Human_GO_BP_Detect_bacterial_geneset
#> # A tibble: 376 × 10
#> GOBP_ANTIBACTERIAL_HUMORAL_RE…¹ GOBP_ANTIBACTERIAL_I…² GOBP_ANTIBACTERIAL_P…³
#> <chr> <chr> <chr>
#> 1 ADM CXCL6 ELANE
#> 2 ANG DEFB136 EVPL
#> 3 APP IL33 KLK3
#> 4 B2M MARCHF2 KLK5
#> 5 BPI MIRLET7B KLK7
#> 6 BPIFA1 MPEG1 LGALS4
#> 7 CALCA NFKB1 MMP7
#> 8 CAMP NOD2 PGC
#> 9 CTSG RASGRP4 SPINK5
#> 10 DEFA1 SLC15A2 NA
#> # ℹ 366 more rows
#> # ℹ abbreviated names: ¹GOBP_ANTIBACTERIAL_HUMORAL_RESPONSE,
#> # ²GOBP_ANTIBACTERIAL_INNATE_IMMUNE_RESPONSE,
#> # ³GOBP_ANTIBACTERIAL_PEPTIDE_PRODUCTION
#> # ℹ 7 more variables:
#> # GOBP_CELLULAR_RESPONSE_TO_MOLECULE_OF_BACTERIAL_ORIGIN <chr>,
#> # GOBP_DETECTION_OF_MOLECULE_OF_BACTERIAL_ORIGIN <chr>, …
#>
#> $Human$Geneset$GO$Human_GO_BP_Detect_viral_geneset
#> # A tibble: 437 × 9
#> GOBP_CELLULAR_RESPONSE_TO_VIRUS GOBP_DEFENSE_RESPONS…¹ GOBP_NEGATIVE_REGULA…²
#> <chr> <chr> <chr>
#> 1 ADAR ABCC9 ATG12
#> 2 ARF1 ABCF3 ATG5
#> 3 ATF2 ACOD1 C1QBP
#> 4 BAX ADAR FGL2
#> 5 CALR ADARB1 FOXP3
#> 6 CCL19 AGBL4 ILRUN
#> 7 CCL5 AGBL5 IRGM
#> 8 CHUK AICDA ITCH
#> 9 CXCL10 AIM2 MICB
#> 10 DDX3X AIMP1 MIR26B
#> # ℹ 427 more rows
#> # ℹ abbreviated names: ¹GOBP_DEFENSE_RESPONSE_TO_VIRUS,
#> # ²GOBP_NEGATIVE_REGULATION_OF_DEFENSE_RESPONSE_TO_VIRUS
#> # ℹ 6 more variables:
#> # GOBP_POSITIVE_REGULATION_OF_DEFENSE_RESPONSE_TO_VIRUS_BY_HOST <chr>,
#> # GOBP_REGULATION_BY_VIRUS_OF_VIRAL_PROTEIN_LEVELS_IN_HOST_CELL <chr>,
#> # GOBP_REGULATION_OF_DEFENSE_RESPONSE_TO_VIRUS <chr>, …
#>
#>
#> $Human$Geneset$Human_MSigDB_Hallmark_geneset
#> # A tibble: 200 × 50
#> HALLMARK_ADIPOGENESIS HALLMARK_ALLOGRAFT_REJECTION HALLMARK_ANDROGEN_RESPONSE
#> <chr> <chr> <chr>
#> 1 ABCA1 AARS1 ABCC4
#> 2 ABCB8 ABCE1 ABHD2
#> 3 ACAA2 ABI1 ACSL3
#> 4 ACADL ACHE ACTN1
#> 5 ACADM ACVR2A ADAMTS1
#> 6 ACADS AKT1 ADRM1
#> 7 ACLY APBB1 AKAP12
#> 8 ACO2 B2M AKT1
#> 9 ACOX1 BCAT1 ALDH1A3
#> 10 ADCY6 BCL10 ANKH
#> # ℹ 190 more rows
#> # ℹ 47 more variables: HALLMARK_ANGIOGENESIS <chr>,
#> # HALLMARK_APICAL_JUNCTION <chr>, HALLMARK_APICAL_SURFACE <chr>,
#> # HALLMARK_APOPTOSIS <chr>, HALLMARK_BILE_ACID_METABOLISM <chr>,
#> # HALLMARK_CHOLESTEROL_HOMEOSTASIS <chr>, HALLMARK_COAGULATION <chr>,
#> # HALLMARK_COMPLEMENT <chr>, HALLMARK_DNA_REPAIR <chr>,
#> # HALLMARK_E2F_TARGETS <chr>, …
#>
#> $Human$Geneset$Human_PCD_geneset
#> # A tibble: 580 × 18
#> Apoptosis Pyroptosis Ferroptosis Autophagy Necroptosis Cuproptosis
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 AATF BAK1 ABCC1 ABL1 GLUD1 NFE2L2
#> 2 ABL1 BAX ACACA ABL2 GLUD2 NLRP3
#> 3 ACAA2 CASP1 ACO1 ACER2 ALOX15 ATP7B
#> 4 ACKR3 CASP3 ACSF2 ADRA1A FTH1 ATP7A
#> 5 ACVR1 CASP4 ACSL1 ADRB2 PYG SLC31A1
#> 6 ACVR1B CASP5 ACSL3 AKT1 CAPN1 FDX1
#> 7 ADORA1 CASP6 ACSL4 AMBRA1 CASP1 LIAS
#> 8 AEN CASP8 ACSL5 ATF6 GLNA LIPT1
#> 9 AGT CASP9 ACSL6 ATG101 BAX LIPT2
#> 10 AGTR2 CHMP2A AIFM2 ATG13 BCL2 DLD
#> # ℹ 570 more rows
#> # ℹ 12 more variables: Parthanatos <chr>, Entoticcelldeath <chr>,
#> # Netoticcelldeath <chr>, `Lysosome-dependentcelldeath` <chr>,
#> # Alkaliptosis <chr>, Oxeiptosis <chr>, NETosis <chr>,
#> # Immunogenic_cell_death <chr>, Anoikis <chr>, Paraptosis <chr>,
#> # Methuosis <chr>, Entosis <chr>
#>
#> $Human$Geneset$KEGG
#> $Human$Geneset$KEGG$Human_KEGG_Detect_bacterial_geneset
#> # A tibble: 253 × 11
#> Bacterial invasion of epithel…¹ Vibrio cholerae infe…² Epithelial cell sign…³
#> <chr> <chr> <chr>
#> 1 ARPC5 ATP6V1FP2 ATP6V1FP2
#> 2 ARPC4 TCIRG1 ADAM10
#> 3 ARPC3 CFTR TCIRG1
#> 4 ARPC1B ADCY3 NOD1
#> 5 ACTR3 KDELR1 CHUK
#> 6 ACTR2 SEC61B ATP6V1G3
#> 7 ARPC2 KDELR2 MAPK14
#> 8 WASF2 KDELR3 CSK
#> 9 MAD2L2 ADCY9 IGSF5
#> 10 ARPC1A ATP6V1G3 ATP6V0E2
#> # ℹ 243 more rows
#> # ℹ abbreviated names: ¹`Bacterial invasion of epithelial cells`,
#> # ²`Vibrio cholerae infection`,
#> # ³`Epithelial cell signaling in Helicobacter pylori infection`
#> # ℹ 8 more variables: `Pathogenic Escherichia coli infection` <chr>,
#> # Shigellosis <chr>, `Salmonella infection` <chr>, Pertussis <chr>,
#> # Legionellosis <chr>, `Yersinia infection` <chr>, …
#>
#> $Human$Geneset$KEGG$Human_KEGG_Detect_parasitic_geneset
#> # A tibble: 112 × 6
#> Leishmaniasis `Chagas disease` African trypanosomiasi…¹ Malaria Toxoplasmosis
#> <chr> <chr> <chr> <chr> <chr>
#> 1 IGH AKT3 IGH KLRC4-… AKT3
#> 2 TAB1 TLR6 IDO2 COMP PPIF
#> 3 FCGR3B ADCY1 F2RL1 CR1 LAMC3
#> 4 CR1 P3R3URF-PIK3R3 PLCB1 CR1L TAB1
#> 5 CR1L CHUK GNAQ CSF3 CHUK
#> 6 MAPK14 MAPK14 HBA1 KLRK1 CCR5
#> 7 CYBA TICAM1 HBA2 ACKR1 MAPK14
#> 8 CYBB ACE HBB GYPA PIK3R6
#> 9 EEF1A1 AKT1 HPR GYPB AKT1
#> 10 EEF1A2 AKT2 APOA1 GYPC AKT2
#> # ℹ 102 more rows
#> # ℹ abbreviated name: ¹`African trypanosomiasis`
#> # ℹ 1 more variable: Amoebiasis <chr>
#>
#> $Human$Geneset$KEGG$Human_KEGG_Detect_viral_geneset
#> # A tibble: 333 × 21
#> `Viral life cycle - HIV-1` Virion - Human immunodefi…¹ Virion - Flavivirus …²
#> <chr> <chr> <chr>
#> 1 PDCD6IP CLEC4M CLEC4M
#> 2 APOBEC3A_B CCR5 HAVCR1
#> 3 CDK9 CD209 CD209
#> 4 SERINC3 CXCR4 PHB1
#> 5 CPSF6 CD4 MXRA8
#> 6 PSIP1 NA TYRO3
#> 7 CCR5 NA NA
#> 8 CHMP4B NA NA
#> 9 CREBBP NA NA
#> 10 APOBEC3D NA NA
#> # ℹ 323 more rows
#> # ℹ abbreviated names: ¹`Virion - Human immunodeficiency virus`,
#> # ²`Virion - Flavivirus and Alphavirus`
#> # ℹ 18 more variables:
#> # `Virion - Ebolavirus, Lyssavirus and Morbillivirus` <chr>,
#> # `Virion - Herpesvirus` <chr>, `Virion - Adenovirus` <chr>,
#> # `Virion - Rotavirus` <chr>, `Virion - Hepatitis viruses` <chr>, …
#>
#> $Human$Geneset$KEGG$Human_KEGG_Metabolism_geneset
#> # A tibble: 136 × 85
#> `Glycolysis / Gluconeogenesis` Citrate cycle (TCA cy…¹ Pentose phosphate pa…²
#> <chr> <chr> <chr>
#> 1 AKR1A1 CS GLYCTK
#> 2 ADH1A DLAT FBP1
#> 3 ADH1B DLD PRPS1L1
#> 4 ADH1C DLST ALDOA
#> 5 ADH4 FH ALDOB
#> 6 ADH5 IDH1 RPIA
#> 7 ADH6 IDH2 ALDOC
#> 8 GALM IDH3A SHPK
#> 9 ADH7 IDH3B G6PD
#> 10 LDHAL6A IDH3G PGLS
#> # ℹ 126 more rows
#> # ℹ abbreviated names: ¹`Citrate cycle (TCA cycle)`,
#> # ²`Pentose phosphate pathway`
#> # ℹ 82 more variables: `Pentose and glucuronate interconversions` <chr>,
#> # `Fructose and mannose metabolism` <chr>, `Galactose metabolism` <chr>,
#> # `Ascorbate and aldarate metabolism` <chr>, `Fatty acid biosynthesis` <chr>,
#> # `Fatty acid elongation` <chr>, `Fatty acid degradation` <chr>, …
#>
#>
#> $Human$Geneset$Reactome
#> $Human$Geneset$Reactome$Human_Reactome_Metabolism_geneset
#> # A tibble: 374 × 301
#> Mitochondrial iron-sulfur clu…¹ The citric acid (TCA…² Reversible hydration…³
#> <chr> <chr> <chr>
#> 1 FDX2 LRPPRC CA5B
#> 2 ISCA2 TRAP1 CA14
#> 3 HSCB ATP5PD CA13
#> 4 FDX1 ATP5MG CA1
#> 5 FDXR ME3 CA2
#> 6 ISCU UQCR11 CA3
#> 7 FXN COX20 CA4
#> 8 GLRX5 NDUFA11 CA5A
#> 9 SLC25A37 COX4I1 CA6
#> 10 LYRM4 COX5B CA7
#> # ℹ 364 more rows
#> # ℹ abbreviated names: ¹`Mitochondrial iron-sulfur cluster biogenesis`,
#> # ²`The citric acid (TCA) cycle and respiratory electron transport`,
#> # ³`Reversible hydration of carbon dioxide`
#> # ℹ 298 more variables: `Inositol phosphate metabolism` <chr>,
#> # `Metabolism of nucleotides` <chr>,
#> # `Integration of energy metabolism` <chr>, …
#>
#>
#>
#>
#> $Mouse
#> $Mouse$Gene
#> $Mouse$Gene$Mouse_Infection_Immunity_gene
#> # A tibble: 85 × 17
#> IFN IRF IFI CXCL CXCR CCL CCR TNF CSF Il NFKB Attacin
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Ifna-ps1 Irf1 Ifit… Cxcl1 Cxcr1 Ccl1 Ccr1 Lta Csf1 Il1rn Nfkb1 Camp
#> 2 Ifnab Irf2 Ifit… Cxcl2 Cxcr2 Ccl2 Ccr1… Tnf Csf1r Il1a Nfkb2 Defa1
#> 3 Ifne Irf2b… Ifit1 Cxcl3 Cxcr3 Ccl3 Ccrl2 Ltb Csf1… Il1b Nfkb… Defa2
#> 4 Ifng Irf2b… Ifit… Cxcl5 Cxcr4 Ccl4 Ccr2 Tnfs… Csf2 Il1b… Nfkb… Defa3
#> 5 Ifnk Irf2b… Ifih1 Cxcl9 Cxcr5 Ccl5 Ccr3 Cd40… Csf2… Il1f… Nfkb… Defa5
#> 6 Ifnz Irf3 Ifit… Cxcl… Cxcr6 Ccl6 Ccr4 Faslg Csf2… Il1r1 Nfkb… Defb1
#> 7 Ifna1 Irf4 Ifit2 Cxcl… NA Ccl7 Ccr5 Cd70 Csf2… Il1r2 Nfkb… Defb2
#> 8 Ifnar1 Irf5 Ifit3 Cxcl… NA Ccl8 Ccr6 Tnfs… Csf3r Il1r… Nfkb… Defb3
#> 9 Ifnb1 Irf6 Ifit… Cxcl… NA Ccl9 Ccr7 Tnfs… Csf3 Il1r… Rel Defb4
#> 10 Ifngas1 Irf7 Ifit… Cxcl… NA Ccl11 Ccr8 Tnfs… NA Il1r… Rela Defb5
#> # ℹ 75 more rows
#> # ℹ 5 more variables: ATE <chr>, ROS_NO <chr>, Clq <chr>, Acute_Phase <chr>,
#> # Antigen <chr>
#>
#> $Mouse$Gene$Mouse_Macrophage_gene
#> # A tibble: 15 × 3
#> M1 M2 Fusion
#> <chr> <chr> <chr>
#> 1 Fcgr3 Cd163 Adam9
#> 2 Cd86 Mrc1 Cd44
#> 3 Cd14 Arg1 Cd81
#> 4 Nos2 Chil3 Dcstamp
#> 5 Il6 Retnla Ocstamp
#> 6 Tnf Il10 Stat1
#> 7 Il1b Tgfb1 Trem2
#> 8 Il12b Pparg Tyrobp
#> 9 Cxcl9 Klf4 NA
#> 10 Cxcl10 Il4ra NA
#> 11 Cd80 Ccl17 NA
#> 12 H2-Aa Ccl22 NA
#> 13 Irf5 NA NA
#> 14 Socs3 NA NA
#> 15 Fpr2 NA NA
#>
#> $Mouse$Gene$Mouse_PRR_gene
#> # A tibble: 37 × 8
#> TLRs TLRs_downstream CASP NLRs CLRs SRs CRs FcRs
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Tlr1 Myd88 Casp1 Citta Mrc1 Msr1 Cr1l Fcgrt
#> 2 Tlr2 Ticam1 Casp2 Naip1 Clec1a Scaf1 Cr2 Fcgr1
#> 3 Tlr3 Ticam2 Casp3 Naip2 Clec1b Cd36 Itgam Fcgr2b
#> 4 Tlr4 Tirap Casp4 Naip3 Clec2m Scarb1 Itgax Fcgr3
#> 5 Cd14 Tram1 Casp6 Naip3-ps1 Clec2d Marco Fcgr1 Fcgr4
#> 6 Tlr5 Tram2 Casp7 Naip5 Clec2e Cd163 NA NA
#> 7 Tlr6 Tram1l1 Casp8 Naip6 Clec2f NA NA NA
#> 8 Tlr7 Traf1 Casp8ap2 Nod1 Clec2g NA NA NA
#> 9 Tlr8 Trafd1 Casp9 Nod2 Clec2h NA NA NA
#> 10 Tlr9 Traf2 Casp12 Nodal Clec2i NA NA NA
#> # ℹ 27 more rows
#>
#>
#> $Mouse$Geneset
#> $Mouse$Geneset$GO
#> $Mouse$Geneset$GO$Mouse_GO_BP_Detect_bacterial_geneset
#> # A tibble: 484 × 7
#> GOBP_ANTIBACTERIAL_HUMORAL_RE…¹ GOBP_ANTIBACTERIAL_I…² GOBP_ANTIBACTERIAL_P…³
#> <chr> <chr> <chr>
#> 1 AY761185 Defb42 Elane
#> 2 Adm Il33 Evpl
#> 3 Ang Marchf2 Ivl
#> 4 Ang2 Mpeg1 Klk5
#> 5 Ang4 Muc19 Klk7
#> 6 Ang5 Nfkb1 Lgals4
#> 7 Ang6 Nod2 Mmp7
#> 8 App Rasgrp4 Nod2
#> 9 B2m Slc15a2 Pgc
#> 10 Bpi Tfeb Ppl
#> # ℹ 474 more rows
#> # ℹ abbreviated names: ¹GOBP_ANTIBACTERIAL_HUMORAL_RESPONSE,
#> # ²GOBP_ANTIBACTERIAL_INNATE_IMMUNE_RESPONSE,
#> # ³GOBP_ANTIBACTERIAL_PEPTIDE_PRODUCTION
#> # ℹ 4 more variables: GOBP_DETECTION_OF_MOLECULE_OF_BACTERIAL_ORIGIN <chr>,
#> # GOBP_REGULATION_OF_ANTIBACTERIAL_PEPTIDE_PRODUCTION <chr>,
#> # GOBP_RESPONSE_TO_BACTERIAL_LIPOPROTEIN <chr>, …
#>
#> $Mouse$Geneset$GO$Mouse_GO_BP_Detect_viral_geneset
#> # A tibble: 367 × 12
#> GOBP_CELLULAR_RESPONSE_TO_VIRUS GOBP_DEFENSE_RESPONS…¹ GOBP_DETECTION_OF_VI…²
#> <chr> <chr> <chr>
#> 1 Adar Abcc9 Ncr1
#> 2 Arf1 Abcf3 Rigi
#> 3 Atf2 Acod1 Serinc3
#> 4 Bax Agbl4 Serinc5
#> 5 Ccl19 Agbl5 Zcchc3
#> 6 Ccl19-ps1 Aicda NA
#> 7 Ccl19-ps3 Aim2 NA
#> 8 Ccl19-ps4 Akap1 NA
#> 9 Ccl19-ps5 Apobec1 NA
#> 10 Ccl19-ps6 Apobec3 NA
#> # ℹ 357 more rows
#> # ℹ abbreviated names: ¹GOBP_DEFENSE_RESPONSE_TO_VIRUS,
#> # ²GOBP_DETECTION_OF_VIRUS
#> # ℹ 9 more variables: GOBP_INTRACELLULAR_TRANSPORT_OF_VIRUS <chr>,
#> # GOBP_NEGATIVE_REGULATION_OF_DEFENSE_RESPONSE_TO_VIRUS <chr>,
#> # GOBP_POSITIVE_REGULATION_OF_DEFENSE_RESPONSE_TO_VIRUS_BY_HOST <chr>,
#> # GOBP_RECEPTOR_MEDIATED_ENDOCYTOSIS_OF_VIRUS_BY_HOST_CELL <chr>, …
#>
#>
#> $Mouse$Geneset$KEGG
#> $Mouse$Geneset$KEGG$Mouse_KEGG_Detect_bacterial_geneset
#> # A tibble: 252 × 7
#> Bacterial invasion of epithe…¹ `Salmonella infection` Pertussis Legionellosis
#> <chr> <chr> <chr> <chr>
#> 1 Dnm3 Dynlt1f Ticam1 Apaf1
#> 2 Actb Dynlt1c Nod1 Arf1
#> 3 Actg1 Ahnak2 Tirap Arf2
#> 4 Rhoa Dynlt1a Rhoa Bnip3
#> 5 Arpc1b Brk1 Serping1 C3
#> 6 Ctnna1 Exoc5 C1qa Casp1
#> 7 Ctnna2 Nckap1l C1qb Casp3
#> 8 Ctnnb1 Nod1 C1qc Casp7
#> 9 Cav1 Raf1 C2 Casp8
#> 10 Cav2 Dync2h1 C3 Casp9
#> # ℹ 242 more rows
#> # ℹ abbreviated name: ¹`Bacterial invasion of epithelial cells`
#> # ℹ 3 more variables: `Yersinia infection` <chr>,
#> # `Staphylococcus aureus infection` <chr>, Tuberculosis <chr>
#>
#> $Mouse$Geneset$KEGG$Mouse_KEGG_Detect_parasitic_geneset
#> # A tibble: 109 × 6
#> Leishmaniasis `Chagas disease` African trypanosomiasi…¹ Malaria Toxoplasmosis
#> <chr> <chr> <chr> <chr> <chr>
#> 1 H2-Ea Ticam1 Hbb-bs Klrb1 H2-Ea
#> 2 C3 Calr4 Hbb-bt Hbb-bs Pik3r6
#> 3 Cr1l Ace Hba-a2 Hbb-bt Ppif
#> 4 Cyba Akt1 Apoa1 Hba-a2 Akt1
#> 5 Cybb Akt2 F2rl1 Cd36 Akt2
#> 6 Eef1a1 Bdkrb2 Fas Cd81 Alox5
#> 7 Eef1a2 C1qa Fasl Comp Birc3
#> 8 Elk1 C1qb Gnaq Cr1l Birc2
#> 9 Fcgr1 C1qc Hba-a1 Csf3 Xiap
#> 10 Fcgr3 C3 Hbb-b1 Ackr1 Bad
#> # ℹ 99 more rows
#> # ℹ abbreviated name: ¹`African trypanosomiasis`
#> # ℹ 1 more variable: Amoebiasis <chr>
#>
#> $Mouse$Geneset$KEGG$Mouse_KEGG_Detect_viral_geneset
#> # A tibble: 359 × 21
#> `Viral life cycle - HIV-1` Virion - Human immunodefi…¹ Virion - Flavivirus …²
#> <chr> <chr> <chr>
#> 1 Supt4b Cd4 Cd209c
#> 2 Psip1 Cxcr4 Cd209d
#> 3 Xpo1 Ccr5 Cd209e
#> 4 Cdk9 Cd209c Cd209a
#> 5 Vps4a Cd209d Havcr1
#> 6 Bicd1 Cd209e Timd2
#> 7 Ccnt1 Cd209a Phb1
#> 8 Cd4 Cd209f Tyro3
#> 9 Cxcr4 Cd209b 1700071K01Rik
#> 10 Ccr5 Cd209g Cd209f
#> # ℹ 349 more rows
#> # ℹ abbreviated names: ¹`Virion - Human immunodeficiency virus`,
#> # ²`Virion - Flavivirus and Alphavirus`
#> # ℹ 18 more variables:
#> # `Virion - Ebolavirus, Lyssavirus and Morbillivirus` <chr>,
#> # `Virion - Herpesvirus` <chr>, `Virion - Adenovirus` <chr>,
#> # `Virion - Rotavirus` <chr>, `Virion - Hepatitis viruses` <chr>, …
#>
#> $Mouse$Geneset$KEGG$Mouse_KEGG_Metabolism_geneset
#> # A tibble: 141 × 85
#> `Glycolysis / Gluconeogenesis` Citrate cycle (TCA cy…¹ Pentose phosphate pa…²
#> <chr> <chr> <chr>
#> 1 Gck Acly H6pd
#> 2 Ldhal6b Aco1 Pgd
#> 3 Aldh7a1 Aco2 Prps2
#> 4 Adh1 Cs Aldoa
#> 5 Adh7 Dld Aldoc
#> 6 Adh5 Fh1 Fbp2
#> 7 Gm29667 Idh1 Fbp1
#> 8 Aldh2 Idh3g G6pd2
#> 9 Aldh3a1 Idh3b G6pdx
#> 10 Aldh3a2 Mdh2 Gpi1
#> # ℹ 131 more rows
#> # ℹ abbreviated names: ¹`Citrate cycle (TCA cycle)`,
#> # ²`Pentose phosphate pathway`
#> # ℹ 82 more variables: `Pentose and glucuronate interconversions` <chr>,
#> # `Fructose and mannose metabolism` <chr>, `Galactose metabolism` <chr>,
#> # `Ascorbate and aldarate metabolism` <chr>, `Fatty acid biosynthesis` <chr>,
#> # `Fatty acid elongation` <chr>, `Fatty acid degradation` <chr>, …
#>
#>
#> $Mouse$Geneset$Mouse_HotSpot_geneset
#> # A tibble: 0 × 2
#> # ℹ 2 variables: Inflammatory <chr>, Immunity <chr>
#>
#> $Mouse$Geneset$Mouse_MSigDB_Hallmark_geneset
#> # A tibble: 200 × 50
#> HALLMARK_ADIPOGENESIS HALLMARK_ALLOGRAFT_REJECTION HALLMARK_ANDROGEN_RESPONSE
#> <chr> <chr> <chr>
#> 1 Abca1 Aars1 Abcc4
#> 2 Abcb8 Abce1 Abhd2
#> 3 Acaa2 Abi1 Acsl3
#> 4 Acadl Ache Actn1
#> 5 Acadm Acvr2a Adamts1
#> 6 Acads Akt1 Adrm1
#> 7 Acly Apbb1 Akap12
#> 8 Aco2 B2m Akt1
#> 9 Acox1 Bcat1 Aldh1a3
#> 10 Adcy6 Bcl10 Ank
#> # ℹ 190 more rows
#> # ℹ 47 more variables: HALLMARK_ANGIOGENESIS <chr>,
#> # HALLMARK_APICAL_JUNCTION <chr>, HALLMARK_APICAL_SURFACE <chr>,
#> # HALLMARK_APOPTOSIS <chr>, HALLMARK_BILE_ACID_METABOLISM <chr>,
#> # HALLMARK_CHOLESTEROL_HOMEOSTASIS <chr>, HALLMARK_COAGULATION <chr>,
#> # HALLMARK_COMPLEMENT <chr>, HALLMARK_DNA_REPAIR <chr>,
#> # HALLMARK_E2F_TARGETS <chr>, …
#>
#> $Mouse$Geneset$Mouse_PCD_geneset
#> # A tibble: 577 × 18
#> Apoptosis Pyroptosis Ferroptosis Autophagy Necroptosis Cuproptosis
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Cd74 Gsdmc Sqle Prkaa1 Dnm1l Dlst
#> 2 Zfp385a Gsdmc2 Fdft1 Snx6 Xiap Atp7a
#> 3 Slc25a5 Gsdmc3 Abcc1 Srebf2 Ifngr2 Dbt
#> 4 Sod1 Gsdmc4 Lpcat3 Gsk3b Ifnar1 Atp7b
#> 5 Gsk3b Gm10053 Ftl1-ps1 Hsp90aa1 Ifnar2 Pdha1
#> 6 Fxn Chmp7 Sat1 Trim27 Tlr3 Dlat
#> 7 Ppp1r13b Chmp3 Gclm Atp6v1a Il33 Fdx1
#> 8 Appl1 Scaf11 Nox1 Pik3c3 Ftl1-ps1 Slc31a1
#> 9 Snai2 Tirap Slc39a14 Gata4 Ifng Nlrp3
#> 10 Mir17 Gsdma3 Zeb1 Tspo Aifm1 Gcsh
#> # ℹ 567 more rows
#> # ℹ 12 more variables: Parthanatos <chr>, Entoticcelldeath <chr>,
#> # Netoticcelldeath <chr>, Lysosome.dependentcelldeath <chr>,
#> # Alkaliptosis <chr>, Oxeiptosis <chr>, NETosis <chr>,
#> # Immunogenic_cell_death <chr>, Anoikis <chr>, Paraptosis <chr>,
#> # Methuosis <chr>, Entosis <chr>
#>
#> $Mouse$Geneset$Reactome
#> $Mouse$Geneset$Reactome$Mouse_Reactome_Metabolism_geneset
#> # A tibble: 260 × 253
#> Mitochondrial iron-sulfur clu…¹ The citric acid (TCA…² Reversible hydration…³
#> <chr> <chr> <chr>
#> 1 Hscb Ndufb4b Car1
#> 2 Fdx1 Sco2 Car2
#> 3 Fdxr Ndufb11 Car3
#> 4 Fxn Ldhal6b Car4
#> 5 Nfs1 Me2 Car5a
#> 6 Lyrm4 Me3 Car6
#> 7 Iscu Glo1 Car7
#> 8 Fdx2 Cox6b1 Car9
#> 9 Isca1 Etfb Car14
#> 10 Glrx5 Etfa Car5b
#> # ℹ 250 more rows
#> # ℹ abbreviated names: ¹`Mitochondrial iron-sulfur cluster biogenesis`,
#> # ²`The citric acid (TCA) cycle and respiratory electron transport`,
#> # ³`Reversible hydration of carbon dioxide`
#> # ℹ 250 more variables: `Inositol phosphate metabolism` <chr>,
#> # `Metabolism of nucleotides` <chr>,
#> # `Integration of energy metabolism` <chr>, …Session information
sessionInfo()
#> R version 4.2.0 (2022-04-22 ucrt)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 22000)
#>
#> Matrix products: default
#>
#> locale:
#> [1] LC_COLLATE=Chinese (Simplified)_China.utf8
#> [2] LC_CTYPE=Chinese (Simplified)_China.utf8
#> [3] LC_MONETARY=Chinese (Simplified)_China.utf8
#> [4] LC_NUMERIC=C
#> [5] LC_TIME=Chinese (Simplified)_China.utf8
#>
#> attached base packages:
#> [1] tcltk stats graphics grDevices utils datasets methods
#> [8] base
#>
#> other attached packages:
#> [1] DynDoc_1.74.0 Biobase_2.58.0 BiocGenerics_0.44.0
#> [4] widgetTools_1.74.0
#>
#> loaded via a namespace (and not attached):
#> [1] ggprism_1.0.5 scattermore_1.2
#> [3] R.methodsS3_1.8.2 SeuratObject_5.3.0
#> [5] ragg_1.3.0 tidyr_1.3.1
#> [7] ggvenn_0.1.19 ggplot2_4.0.2
#> [9] bit64_4.0.5 knitr_1.49
#> [11] irlba_2.3.5.1 DelayedArray_0.24.0
#> [13] R.utils_2.12.3 data.table_1.15.4
#> [15] doParallel_1.0.17 KEGGREST_1.36.0
#> [17] RCurl_1.98-1.14 generics_0.1.3
#> [19] cowplot_1.1.3 RSQLite_2.3.6
#> [21] shadowtext_0.1.2 RANN_2.6.1
#> [23] proxy_0.4-27 imager_0.45.8
#> [25] future_1.33.1 chron_2.3-61
#> [27] bit_4.0.5 enrichplot_1.18.3
#> [29] spatstat.data_3.0-4 ggdensity_1.0.0
#> [31] httpuv_1.6.12 assertthat_0.2.1
#> [33] SummarizedExperiment_1.28.0 viridis_0.6.4
#> [35] STRINGdb_2.18.0 xfun_0.49
#> [37] jquerylib_0.1.4 evaluate_1.0.1
#> [39] promises_1.5.0 fansi_1.0.6
#> [41] caTools_1.18.2 igraph_2.0.3
#> [43] DBI_1.2.2 htmlwidgets_1.6.4
#> [45] spatstat.geom_3.2-9 stats4_4.2.0
#> [47] paletteer_1.5.0 purrr_1.0.2
#> [49] hash_2.2.6.3 RSpectra_0.16-1
#> [51] ggnewscale_0.4.9 dplyr_1.1.4
#> [53] annotate_1.76.0 deldir_2.0-4
#> [55] sparseMatrixStats_1.10.0 MatrixGenerics_1.10.0
#> [57] vctrs_0.6.5 SingleCellExperiment_1.20.1
#> [59] SeuratDisk_0.0.0.9021 ROCR_1.0-11
#> [61] abind_1.4-8 cachem_1.1.0
#> [63] withr_3.0.2 ggforce_0.4.1
#> [65] HDO.db_0.99.1 ggh4x_0.2.8
#> [67] progressr_0.14.0 sctransform_0.4.1
#> [69] treeio_1.22.0 mnormt_2.1.1
#> [71] goftest_1.2-3 cluster_2.1.4
#> [73] DOSE_3.24.2 ape_5.8
#> [75] dotCall64_1.1-1 lazyeval_0.2.2
#> [77] crayon_1.5.3 hdf5r_1.3.9
#> [79] spatstat.explore_3.2-7 pkgconfig_2.0.3
#> [81] tweenr_2.0.2 GenomeInfoDb_1.34.9
#> [83] nlme_3.1-162 rlang_1.1.7
#> [85] globals_0.16.3 lifecycle_1.0.5
#> [87] miniUI_0.1.1.1 rBLAST_1.3.1
#> [89] downloader_0.4 dbscan_1.1-11
#> [91] fastDummies_1.7.3 dichromat_2.0-0.1
#> [93] bmp_0.3 polyclip_1.10-6
#> [95] RcppHNSW_0.6.0 matrixStats_1.1.0
#> [97] lmtest_0.9-40 tiff_0.1-12
#> [99] graph_1.76.0 Matrix_1.6-5
#> [101] aplot_0.1.10 tkWidgets_1.74.0
#> [103] zoo_1.8-12 ggridges_0.5.6
#> [105] rjson_0.2.21 png_0.1-8
#> [107] viridisLite_0.4.2 bitops_1.0-7
#> [109] R.oo_1.26.0 gson_0.1.0
#> [111] KernSmooth_2.23-22 spam_2.10-0
#> [113] anndata_0.7.5.6 Biostrings_2.66.0
#> [115] blob_1.2.4 DelayedMatrixStats_1.20.0
#> [117] stringr_1.5.1 qvalue_2.30.0
#> [119] parallelly_1.37.1 spatstat.random_3.2-3
#> [121] jpeg_0.1-10 gridGraphics_0.5-1
#> [123] S4Vectors_0.36.2 ggsignif_0.6.4
#> [125] scales_1.4.0 memoise_2.0.1
#> [127] GSEABase_1.60.0 magrittr_2.0.3
#> [129] plyr_1.8.9 ica_1.0-3
#> [131] gplots_3.1.3.1 zlibbioc_1.44.0
#> [133] compiler_4.2.0 scatterpie_0.2.1
#> [135] Mfuzz_2.56.0 concaveman_1.2.0
#> [137] RColorBrewer_1.1-3 plotrix_3.8-2
#> [139] fitdistrplus_1.1-11 cli_3.6.5
#> [141] XVector_0.38.0 listenv_0.9.1
#> [143] patchwork_1.3.0 pbapply_1.7-2
#> [145] MASS_7.3-60 otel_0.2.0
#> [147] tidyselect_1.2.1 stringi_1.8.3
#> [149] textshaping_0.3.6 yaml_2.3.10
#> [151] GOSemSim_2.24.0 ggrepel_0.9.5
#> [153] grid_4.2.0 sass_0.4.9
#> [155] fastmatch_1.1-3 tools_4.2.0
#> [157] future.apply_1.11.3 STID_0.0.0.9000
#> [159] parallel_4.2.0 rstudioapi_0.15.0
#> [161] foreach_1.5.2 AUCell_1.28.0
#> [163] gridExtra_2.3 farver_2.1.2
#> [165] Rtsne_0.17 ggraph_2.1.0
#> [167] digest_0.6.35 FNN_1.1.4.1
#> [169] shiny_1.13.0 proto_1.0.0
#> [171] Rcpp_1.0.11 GenomicRanges_1.50.2
#> [173] later_1.3.2 RcppAnnoy_0.0.22
#> [175] readbitmap_0.1.5 httr_1.4.7
#> [177] AnnotationDbi_1.60.2 psych_2.4.3
#> [179] distances_0.1.10 colorspace_2.1-0
#> [181] XML_3.99-0.16.1 fs_1.6.3
#> [183] tensor_1.5 reticulate_1.45.0
#> [185] IRanges_2.32.0 splines_4.2.0
#> [187] uwot_0.2.2 yulab.utils_0.0.6
#> [189] rematch2_2.1.2 tidytree_0.4.4
#> [191] spatstat.utils_3.0-4 pkgdown_2.2.0
#> [193] graphlayouts_1.1.1 sp_2.1-3
#> [195] ggplotify_0.1.1 plotly_4.10.4
#> [197] systemfonts_1.0.4 xtable_1.8-4
#> [199] jsonlite_1.8.8 ggtree_3.6.2
#> [201] tidygraph_1.2.3 ggfun_0.1.1
#> [203] R6_2.6.1 gsubfn_0.7
#> [205] pillar_1.9.0 htmltools_0.5.8.1
#> [207] mime_0.12 glue_1.8.0
#> [209] fastmap_1.2.0 clusterProfiler_4.6.2
#> [211] BiocParallel_1.30.4 codetools_0.2-19
#> [213] fgsea_1.22.0 furrr_0.3.1
#> [215] utf8_1.2.4 lattice_0.21-8
#> [217] bslib_0.8.0 spatstat.sparse_3.0-3
#> [219] tibble_3.2.1 sqldf_0.4-11
#> [221] gtools_3.9.5 zip_2.3.0
#> [223] GO.db_3.16.0 S7_0.2.0
#> [225] survival_3.5-5 rmarkdown_2.29
#> [227] desc_1.4.3 GenomeInfoDbData_1.2.9
#> [229] iterators_1.0.14 UCell_2.0.1
#> [231] shinycssloaders_1.1.0 reshape2_1.4.4
#> [233] gtable_0.3.6 Seurat_5.4.0