gene_x 0 like s 346 view s
Tags: R, RNA-seq
#------------------------------
#---- 1. prepare gene sets ----
library(org.Hs.eg.db)
library(dplyr)
library(AnnotationDbi)
#1. Platelets
data <- data.frame(
geneSymbol = c("GP1BA","GP5","GP6","GP9","LY6G6D","MMRN1","PEAR1","PF4","PF4V1","PPBP","SLC35D3"),
geneEntrezID = c("2811","2814","51206","2815","58530","22915","375033","5196","5197","5473","340146"),
GeneSet = rep("Platelets", 11)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Platelets.csv", row.names = FALSE)
#2. Granulocytes
data <- data.frame(
geneSymbol = c("CXCR2","CD177","CLC","CTSS","DEFA1","FUT7","LTB4R","MMP25","OSM","RETN"),
geneEntrezID = c("3579","57126","1178","1520","1667","2529","1241","64386","5008","56729"),
GeneSet = rep("Granulocytes", 10)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Granulocytes.csv", row.names = FALSE)
#3. LDG
data <- data.frame(
geneSymbol = c("AZU1","CAMP","CEACAM6","CEACAM8","CTSG","DEFA4","ELANE","LCN2","LTF","MPO","OLFM4","RNASE3"),
geneEntrezID = c("566","820","4680","1088","1511","1669","1991","3934","4057","4353","10562","6037"),
GeneSet = rep("LDG", 12)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "LDG.csv", row.names = FALSE)
#4. pDC
data <- data.frame(
geneSymbol = c("CLEC4C","NRP1"),
geneEntrezID = c("170482","8829"),
GeneSet = rep("pDC", 2)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "pDC.csv", row.names = FALSE)
#5. Anti-inflammation
data <- data.frame(
geneSymbol = c("IL1RN","TNFAIP3","SOCS3"),
geneEntrezID = c("3557","7128","9021"),
GeneSet = rep("Anti-inflammation", 3)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Anti-inflammation.csv", row.names = FALSE)
#6. Pro-inflam. IL-1
data <- data.frame(
geneSymbol = c("IL1A","IL1B","IL18","IL36A","IL36B","IL36G","IL33","IL1R1","IL1RAP","IL18R1","IL18RAP"),
geneEntrezID = c("3552","3553","3606","27179","27177","56300","90865","3554","3556","8809","8807"),
GeneSet = rep("Pro-inflam. IL-1", 11)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Pro-inflam._IL-1.csv", row.names = FALSE)
#7. Dendritic cells
data <- data.frame(
geneSymbol = c("CLEC12A","CLEC10A","CLEC9A","CSF1R","IGIP","LILRA4","LY75","XCR1"),
geneEntrezID = c("160364","10462","283420","1436","492311","23547","4065","2829"),
GeneSet = rep("Dendritic cells", 8)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Dendritic_cells.csv", row.names = FALSE)
#8. MHC II
data <- data.frame(
geneSymbol = c("HLA-DMA","HLA-DMB","HLA-DPA1","HLA-DPB1","HLA-DPB2","HLA-DQA1","HLA-DQA2","HLA-DQB1","HLA-DQB2","HLA-DRA","HLA-DRB1","HLA-DRB3","HLA-DRB4","HLA-DRB5","HLA-DRB6"),
geneEntrezID = c("3108","3109","3113","3115","3116","3117","3118","3119","3120","3122","3123","3125","3126","3127","3128"),
GeneSet = rep("MHC II", 15)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "MHC_II.csv", row.names = FALSE)
#9. Alt. complement
data <- data.frame(
geneSymbol = c("C3","C5","C6","C7","C8A","C9","CFB","CFD","CFH","CFHR5","CFP","CR1","GZMM","MIR520B","MIR520E","VSIG4"),
geneEntrezID = c("718","727","729","730","731","735","629","1675","3075","81494","5199","1378","3004","574473","574461","11326"),
GeneSet = rep("Alt. complement", 16)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Alt._complement.csv", row.names = FALSE)
#10. TNF
data <- data.frame(
geneSymbol = c("BRCA1","CASP1","CXCL1","CXCL2","GBP1","GP1BA","IFI44","IL18","IL1B","IL1RN","MX1","NAMPT","NR3C1","OAS3","PATJ","SH3BP5","TAP2","TNF","TNFAIP3","TNFRSF11A","WT1","ACLY","ACSL1","ADGRE2","AK3","AKAP10","AMPD3","APOL3","ARID3A","ARSE","ASAP1","B4GALT5","BCL2A1","BHLHE41","BHMT","BIRC3","CALD1","CASP10","CCL15","CCL20","CCL23","CCL3L1","CD37","CD38","CD83","CDKN3","CKB","CR2","CTNND2","CXCL3","CXCL8","CYP27B1","DAB2","EBI3","EGR1","EGR2","EPB41","EREG","ETAA1","F3","FABP1","FBXL2","FCER2","FCGR2A","FLJ11129","FLNA","G0S2","GCH1","GJB2","GLS","GMIP","GRK3","HCAR3","HHEX","HOMER2","HP","ICAM1","IDO1","IKBKG","IL16","IL1A","IL6","INHBA","INSIG1","ITGA6","KITLG","KLF1","KMO","LGALS3BP","MAP3K4","MARCKS","MGLL","MMP19","MN1","MRPS15","MSC","MTF1","NELL2","NFKB1","NFKB2","NFKBIA","NFKBIZ","NKX3-2","PDE4DIP","PDPN","PIAS4","PLAUR","PTGES","PTGS2","RELB","RPGR","RPS9","SDC4","SERPIND1","SFRP1","SLAMF1","SLC30A4","SOD2","SPI1","SSPN","STAT4","TAF15","TBX3","TFF1","TNFAIP2","TRAF1","TSC22D1","TYROBP","UBE2C","VEGFA"),
geneEntrezID = c("672","834","2919","2920","2633","2811","10561","3606","3553","3557","4599","10135","2908","4940","10207","9467","6891","7124","7128","8792","7490","47","2180","30817","50808","11216","272","80833","1820","415","50807","9334","597","79365","635","330","800","843","6359","6364","6368","6349","951","952","9308","1033","1152","1380","1501","2921","3576","1594","1601","10148","1958","1959","2035","2069","54465","2152","2168","25827","2208","2212","54674","2316","50486","2643","2706","2744","51291","157","8843","3087","9455","3240","3383","3620","8517","3603","3552","3569","3624","3638","3655","4254","10661","8564","3959","4216","4082","11343","4327","4330","64960","9242","4520","4753","4790","4791","4792","64332","579","9659","10630","51588","5329","9536","5743","5971","6103","6203","6385","3053","6422","6504","7782","6648","6688","8082","6775","8148","6926","7031","7127","7185","8848","7305","11065","7422"),
GeneSet = rep("TNF", 130)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "TNF.csv", row.names = FALSE)
#11. NLRP3 inflammasome
data <- data.frame(
geneSymbol = c("APP","ATAT1","CARD8","CASP1","CASP4","CD36","CPTP","DHX33","EIF2AK2","GBP5","GSDMD","HSP90AB1","MEFV","NFKB1","NFKB2","NLRC3","NLRP3","P2RX7","PANX1","PSTPIP1","PYCARD","PYDC2","RELA","SIRT2","SUGT1","TLR4","TLR6","TXN","TXNIP","USP50"),
geneEntrezID = c("351","79969","22900","834","837","948","80772","56919","5610","115362","79792","3326","4210","4790","4791","197358","114548","5027","24145","9051","29108","152138","5970","22933","10910","7099","10333","7295","10628","373509"),
GeneSet = rep("NLRP3 inflammasome", 30)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "NLRP3_inflammasome.csv", row.names = FALSE)
#12. Unfolded protein
data <- data.frame(
geneSymbol = c("B4GALT3","CALR","CALU","CANX","CDS2","CHST12","CHST2","DERL1","DERL2","DNAJC3","EDEM2","EDEM3","EMC9","ERAP1","ERGIC2","ERO1L","EXT1","GALNT2","GOLT1B","HERPUD1","HYOU1","IER3IP1","IMPAD1","KDELC1","KDELR2","LMAN2","LPGAT1","MAN1A1","MANEA","MANF","NUCB2","PDIA4","PDIA6","PIGK","PPIB","SEC24D","SEC61G","SPCS3","SSR1","SSR3","TRAM1","TRAM2","UGGT1","XBP1"),
geneEntrezID = c("8703","811","813","821","8760","55501","9435","79139","51009","5611","55741","80267","51016","51752","51290","30001","2131","2590","51026","9709","10525","51124","54928","79070","11014","10960","9926","4121","79694","7873","4925","9601","10130","10026","5479","9871","23480","60559","6745","6747","23471","9697","56886","7494"),
GeneSet = rep("Unfolded protein", 44)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Unfolded_protein.csv", row.names = FALSE)
#13. B cells
data <- data.frame(
geneSymbol = c("IGHD","SH3BP5","BANK1","BLK","BLNK","CD19","CD22","CD79A","CD79B","DAPP1","FCRL1","FCRL2","FCRL3","FCRLA","GON4L","GPR183","IGHM","KLHL6","MS4A1","PAX5","PLCL2","VPREB1","ZNF318"),
geneEntrezID = c("3495","9467","55024","640","29760","930","933","973","974","27071","115350","79368","115352","84824","54856","1880","3507","89857","931","5079","23228","7441","24149"),
GeneSet = rep("B cells", 23)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "B_cells.csv", row.names = FALSE)
#14. Monocyte cell surface
data <- data.frame(
geneSymbol = c("CD14","CD300C","CD33","CD68","CLEC12A","CLEC4D","CLEC4E","FCGR1A","FCGR1B","FCGR3B","LILRA5","LILRA6","LILRB2","LILRB3","OSCAR","SEMA4A","SIGLEC1"),
geneEntrezID = c("929","10871","945","968","160364","338339","26253","2209","2210","2215","353514","79168","10288","11025","126014","64218","6614"),
GeneSet = rep("Monocyte cell surface", 17)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Monocyte_cell_surface.csv", row.names = FALSE)
#15. Inflammasome
data <- data.frame(
geneSymbol = c("CASP1","AIM2","CASP5","CTSB","GSDMB","GSDMD","NAIP","NEK7","NLRC4","NLRP1","NLRP3","NOD2","P2RX7","PANX1","PYCARD","RIPK1"),
geneEntrezID = c("834","9447","838","1508","55876","79792","4671","140609","58484","22861","114548","64127","5027","24145","29108","8737"),
GeneSet = rep("Inflammasome", 16)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Inflammasome.csv", row.names = FALSE)
#16. Monocytes_40
data <- data.frame(
geneSymbol = c("C1QA","C1QB","C1QC","C1RL","CCL2","CCL8","CD14","CD300C","CD33","CD68","CLEC12A","CLEC4D","CLEC4E","CXCL1","CXCL2","CXCR2","FCGR1A","FCGR1B","FCGR3B","GRN","IK","IL18RAP","IL1B","IL1RN","LILRA5","LILRA6","LILRB2","LILRB3","OSCAR","S100A8","SEMA4A","SIGLEC1","THBD","BST1","C1R","CD163","CSF2","FUT4","MNDA","MRC1"),
geneEntrezID = c("712","713","714","51279","6347","6355","929","10871","945","968","160364","338339","26253","2919","2920","3579","2209","2210","2215","2896","3550","8807","3553","3557","353514","79168","10288","11025","126014","6279","64218","6614","7056","683","715","9332","1437","2526","4332","4360"),
GeneSet = rep("Monocytes_40", 40)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Monocytes_40.csv", row.names = FALSE)
#17. Monocyte secreted
data <- data.frame(
geneSymbol = c("C1QA","C1QB","C1QC","C1RL","CCL2","CCL8","CXCL1","CXCL2","GRN","IK","IL18RAP","IL1B","IL1RN","S100A8","THBD","TNF","CXCL10"),
geneEntrezID = c("712","713","714","51279","6347","6355","2919","2920","2896","3550","8807","3553","3557","6279","7056","7124","3627"),
GeneSet = rep("Monocyte secreted", 17)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Monocyte_secreted.csv", row.names = FALSE)
#18. IL-1 cytokines
data <- data.frame(
geneSymbol = c("IL18","IL1B"),
geneEntrezID = c("3606","3553"),
GeneSet = rep("IL-1 cytokines", 2)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "IL-1_cytokines.csv", row.names = FALSE)
#19. SNOR low UP
data <- data.frame(
geneSymbol = c("FCGR1A","CEACAM1","LGALS1","SNORD24","SNORD44","SNORD47","SNORD80"),
geneEntrezID = c("2209","634","3956","26820","26806","26802","26774"),
GeneSet = rep("SNOR low UP", 7)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "SNOR_low_UP.csv", row.names = FALSE)
#20. CD40 activated
data <- data.frame(
geneSymbol = c("BUB1B","CCL22","CD58","DBI","DUSP4","FABP5","FDPS","FEN1","GAPDH","GARS","GRHPR","H2AFX","H2AFZ","HMGB2","HMMR","HPRT1","IMPDH2","LDHA","LDHB","LMNB1","LPXN","MCM2","MCM3","MCM6","MSH6","MTHFD2","MYBL2","NDC80","NME1","PAICS","PCNA","PKM","PRDX3","RFTN1","RGS10","SLAMF1","TK1","TOP2A","TPX2","TRAF1","TUBA1B","TXN","TYMS","UBE2S","VDAC1","WEE1","WSB2","ZWINT"),
geneEntrezID = c("701","6367","965","1622","1846","2171","2224","2237","2597","2617","9380","3014","3015","3148","3161","3251","3615","3939","3945","4001","9404","4171","4172","4175","2956","10797","4605","10403","4830","10606","5111","5315","10935","23180","6001","6504","7083","7153","22974","7185","10376","7295","7298","27338","7416","7465","55884","11130"),
GeneSet = rep("CD40 activated", 48)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "CD40_activated.csv", row.names = FALSE)
#21. Lectin complement
data <- data.frame(
geneSymbol = c("A2M","C2","C3","C4A","C4B","C4B_2","C5","C6","C7","C8A","C9","COLEC10","COLEC11","FCN1","FCN2","FCN3","KRT1","MASP1","MASP2","MBL2","SERPING1"),
geneEntrezID = c("2","717","718","720","721","100293534","727","729","730","731","735","10584","78989","2219","2220","8547","3848","5648","10747","4153","710"),
GeneSet = rep("Lectin complement", 21)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Lectin_complement.csv", row.names = FALSE)
#22. Classical complement
data <- data.frame(
geneSymbol = c("C1QA","CIQB","C1QC","C1R","C1S","C2","C3","C4A","C4B","C4B_2","C5","C6","C7","C8A","C9"),
geneEntrezID = c("712","713","714","715","716","717","718","720","721","100293534","727","729","730","731","735"),
GeneSet = rep("Classical complement", 15)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Classical_complement.csv", row.names = FALSE)
#23. Cell cycle
data <- data.frame(
geneSymbol = c("BRCA1","ASPM","AURKA","AURKB","CCNB1","CCNB2","CCNE1","CDC20","CENPM","CEP55","E2F3","GINS2","MCM10","MCM2","MKI67","NCAPG","NDC80","PTTG1","TYMS"),
geneEntrezID = c("672","259266","6790","9212","891","9133","898","991","79019","55165","1871","51659","55388","4171","4288","64151","10403","9232","7298"),
GeneSet = rep("Cell cycle", 19)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Cell_cycle.csv", row.names = FALSE)
#24. Plasma cells
data <- data.frame(
geneSymbol = c("IGHV4-28","IGHV4-34","IGHD","IGHG1","IGHV2-5","IGHV3-20","IGHV3-23","IGKC","IGLV1-40","IGLV3-1","IGLV3-19","IGLV3-25","IGLV4-3","IGLV4-60","IGLV5-45","IGLV6-57","IGLVI-70","C19orf10","IGH","IGHMBP2","IGHV4-31","IGK","IGL","IGLJ3","IGLL1","IGLV@","IGLV1-44","IGLV2-14","IGLV2-5","MZB1","PRDM1","SDC1","THEMIS2","TNFRSF17"),
geneEntrezID = c("28400","28395","3495","3500","28457","28445","28442","3514","28825","28809","28797","28793","28786","28785","28781","28778","28763","56005","3492","3508","28396","50802","3535","28831","3543","3546","28823","28815","28818","51237","639","6382","9473","608"),
GeneSet = rep("Plasma cells", 34)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Plasma_cells.csv", row.names = FALSE)
#25. IG chains
data <- data.frame(
geneSymbol = c("IGHG1","IGHV2-5","IGHV3-20","IGHV3-23","IGHV4-28","IGHV4-34","IGKC","IGLV1-40","IGLV3-1","IGLV3-19","IGLV3-25","IGLV4-3","IGLV4-60","IGLV5-45","IGLV6-57","IGLVI-70","IGHA1","IGHA2","IGHD2-15","IGHD2-2","IGHD2-21","IGHD3-10","IGHD3-16","IGHD3-3","IGHD3-9","IGHG2","IGHG3","IGHG4","IGHJ1","IGHJ2","IGHJ3","IGHJ4","IGHJ5","IGHJ6","IGHV1-18","IGHV1-2","IGHV1-24","IGHV1-3","IGHV1-45","IGHV1-46","IGHV1-58","IGHV1-69-2","IGHV2-26","IGHV2-70","IGHV3-13","IGHV3-15","IGHV3-21","IGHV3-33","IGHV3-43","IGHV3-48","IGHV3-49","IGHV3-53","IGHV3-62","IGHV3-64","IGHV3-7","IGHV3-72","IGHV3-73","IGHV3-74","IGHV4-30-2","IGHV4-39","IGHV4-59","IGHV4-61","IGHV5-51","IGHV6-1","IGHV7-81","IGKJ1","IGKJ2","IGKJ3","IGKJ4","IGKJ5","IGKV1-16","IGKV1-17","IGKV1-27","IGKV1-5","IGKV1-6","IGKV1-9","IGKV1D-16","IGKV1D-17","IGKV1D-43","IGKV1D-8","IGKV2-24","IGKV2D-26","IGKV2D-29","IGKV2D-30","IGKV3-20","IGKV3D-20","IGKV3D-7","IGKV4-1","IGKV5-2","IGLC2","IGLC7","IGLJ6","IGLV10-54","IGLV1-36","IGLV1-47","IGLV2-11","IGLV2-18","IGLV2-23","IGLV2-33","IGLV2-8","IGLV3-10","IGLV3-12","IGLV3-16","IGLV3-21","IGLV3-27","IGLV3-32","IGLV4-69","IGLV5-37","IGLV7-43","IGLV8-61","IGLV9-49"),
geneEntrezID = c("3500","28457","28445","28442","28400","28395","3514","28825","28809","28797","28793","28786","28785","28781","28778","28763","3493","3494","28503","28505","28502","28499","28498","28501","28500","3501","3502","3503","28483","28481","28479","28477","28476","28475","28468","28474","28467","28473","28466","28465","28464","28458","28455","28454","28449","28448","28444","28434","28426","28424","28423","28420","28416","28414","28452","28410","28409","28408","28398","28394","28392","28391","28388","28385","28378","28950","28949","28948","28947","28946","28938","28937","28935","28299","28943","28941","28901","28900","28891","28904","28923","28884","28882","28881","28912","28874","28877","28908","28907","3538","28834","28828","28772","28826","28822","28816","28814","28813","28811","28817","28803","28802","28799","28796","28791","28787","28784","28783","28776","28774","28773"),
GeneSet = rep("IG chains", 111)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "IG_chains.csv", row.names = FALSE)
#26. Erythrocytes
data <- data.frame(
geneSymbol = c("EPO","GFI1B","GYPA","GYPB","GYPE","ICAM4","NFE2","SLC4A1","TRIM10","TSPO2","ZNF367"),
geneEntrezID = c("2056","8328","2993","2994","2996","3386","4778","6521","10107","222642","195828"),
GeneSet = rep("Erythrocytes", 11)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Erythrocytes.csv", row.names = FALSE)
#27. IL-6R complex
data <- data.frame(
geneSymbol = c("IL6","IL6R","IL6ST"),
geneEntrezID = c("3569","3570","3572"),
GeneSet = rep("IL-6R complex", 3)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "IL-6R_complex.csv", row.names = FALSE)
#28. IFN
data <- data.frame(
geneSymbol = c("EIF2AK2","GBP1","GBP2","GBP4","HERC5","HERC6","IFI27","IFI30","IFI35","IFI44","IFI44L","IFI6","IFIT1","IFIT2","IFIT3","IFIT5","IFITM1","IFITM2","IFITM3","ISG15","ISG20","MX1","MX2","OAS1","OAS2","OAS3","OASL","RSAD2","SAMD9","SAMD9L","SP100","SP110"),
geneEntrezID = c("5610","2633","2634","115361","51191","55008","3429","10437","3430","10561","10964","2537","3434","3433","3437","24138","8519","10581","10410","9636","3669","4599","4600","4938","4939","4940","8638","91543","54809","219285","6672","3431"),
GeneSet = rep("IFN", 32)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "IFN.csv", row.names = FALSE)
#29. TCRB
data <- data.frame(
geneSymbol = c("TRBC2","TRBJ2-1","TRBJ2-2","TRBJ2-2P","TRBJ2-3","TRBJ2-4","TRBJ2-5","TRBJ2-6","TRBJ2-7","TRBV1","TRBV10-1","TRBV10-2","TRBV11-1","TRBV11-2","TRBV19","TRBV2","TRBV20-1","TRBV21-1","TRBV23-1","TRBV24-1","TRBV25-1","TRBV27","TRBV28","TRBV3-1","TRBV4-1","TRBV4-2","TRBV5-1","TRBV5-3","TRBV5-4","TRBV5-5","TRBV5-6","TRBV5-7","TRBV6-1","TRBV6-4","TRBV6-5","TRBV6-6","TRBV6-7","TRBV6-8","TRBV7-1","TRBV7-3","TRBV7-4","TRBV7-5","TRBV7-6","TRBV7-7","TRBV9"),
geneEntrezID = c("28638","28629","28628","28627","28626","28625","28624","28623","28622","28621","28585","28584","28582","28581","28568","28620","28567","28566","28564","28563","28562","28560","28559","28619","28617","28616","28614","28612","28611","28610","28609","28608","28606","28603","28602","28601","28600","28599","28597","28595","28594","28593","28592","28591","28586"),
GeneSet = rep("TCRB", 45)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "TCRB.csv", row.names = FALSE)
#30. TCRA
data <- data.frame(
geneSymbol = c("TRAV10","TRAV1-1","TRAV1-2","TRAV12-1","TRAV12-2","TRAV12-3","TRAV13-1","TRAV13-2","TRAV14DV4","TRAV16","TRAV17","TRAV18","TRAV19","TRAV2","TRAV20","TRAV21","TRAV22","TRAV23DV6","TRAV24","TRAV25","TRAV26-1","TRAV26-2","TRAV27","TRAV29DV5","TRAV3","TRAV30","TRAV34","TRAV35","TRAV36DV7","TRAV38-1","TRAV38-2DV8","TRAV39","TRAV4","TRAV40","TRAV41","TRAV5","TRAV7","TRAV8-1","TRAV8-2","TRAV8-3","TRAV8-4","TRAV8-6","TRAV8-7","TRAV9-1","TRAV9-2"),
geneEntrezID = c("28676","28693","28692","28674","28673","28672","28671","28670","28669","28667","28666","28665","28664","28691","28663","28662","28661","28660","28659","28658","28657","28656","28655","28653","28690","28652","28648","28647","28646","28644","28643","28642","28689","28641","28640","28688","28686","28685","28684","28683","28682","28680","28679","28678","28677"),
GeneSet = rep("TCRA", 45)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "TCRA.csv", row.names = FALSE)
#31. Cyt. act. T cells
data <- data.frame(
geneSymbol = c("GZMB","TAGAP","CD69","EOMES","GZMH","IFNG","IL2RB","PRF1","SGK1","TBX21","TFRC","ZNF683"),
geneEntrezID = c("3002","117289","969","8320","2999","3458","3560","5551","6446","30009","7037","257101"),
GeneSet = rep("Cyt. act. T cells", 12)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Cyt._act._T_cells.csv", row.names = FALSE)
#32. TCRG
data <- data.frame(
geneSymbol = c("TRGC2","TRGV1","TRGV10","TRGV11","TRGV2","TRGV3","TRGV4","TRGV5","TRGV7","TRGV8","TRGV9"),
geneEntrezID = c("6967","6973","6984","6985","6974","6976","6977","6978","6981","6982","6983"),
GeneSet = rep("TCRG", 11)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "TCRG.csv", row.names = FALSE)
#33. T cells
data <- data.frame(
geneSymbol = c("CD8A","CD8B","TRDC","CCR3","CD226","CD247","CD28","CD3D","CD3E","CD3G","CD4","CD5","ETS1","GATA3","GRAP2","LEF1","SH2D1A","TRAC","TRBC1"),
geneEntrezID = c("925","926","28526","1232","10666","919","940","915","916","917","920","921","2113","2625","9402","51176","4068","28755","28639"),
GeneSet = rep("T cells", 19)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "T_cells.csv", row.names = FALSE)
#34. CD8T-NK-NKT
data <- data.frame(
geneSymbol = c("CD8A","CD8B","GZMB","NKTR","CD2","CD7","CRTAM","GNLY","GZMA","GZMK","GZMM","HCST","KIR2DL3","KIR3DL1","KIR3DL2","KLRB1","KLRC3","KLRC4","KLRD1","NKG7","RASAL3","TIA1","TXK"),
geneEntrezID = c("925","926","3002","4820","914","924","56253","10578","3001","3003","3004","10870","3804","3811","3812","3820","3823","8302","3824","4818","64926","7072","7294"),
GeneSet = rep("CD8T-NK-NKT", 23)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "CD8T-NK-NKT.csv", row.names = FALSE)
#35. Anergic or act. T cells
data <- data.frame(
geneSymbol = c("CD160","CD244","CTLA4","HAVCR2","ICOS","KLRG1","LAG3","PDCD1"),
geneEntrezID = c("11126","51744","1493","84868","29851","10219","3902","5133"),
GeneSet = rep("Anergic or act. T cells", 8)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Anergic_or_act._T_cells.csv", row.names = FALSE)
#36. T activated
data <- data.frame(
geneSymbol = c("FASLG","TAGAP","CD40LG","CREM","IL17A","IL17F","IL23R","JAKMIP1","KCNA3","KCNN4","P2RX5","PRKCQ","RELT","RNF125","SATB1","TNFRSF4","TNFRSF9"),
geneEntrezID = c("356","117289","959","1390","3605","112744","149233","152789","3738","3783","5026","5588","84957","54941","6304","7293","3604"),
GeneSet = rep("T activated", 17)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "T_activated.csv", row.names = FALSE)
#37. NK cells
data <- data.frame(
geneSymbol = c("KLRF1","NCAM1","NCR1","NCR3","SH2D1B"),
geneEntrezID = c("51348","4684","9437","259197","117157"),
GeneSet = rep("NK cells", 5)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "NK_cells.csv", row.names = FALSE)
#38. TCRD
data <- data.frame(
geneSymbol = c("TRDC","TRDJ1","TRDJ2","TRDJ3","TRDJ4","TRDV1","TRDV2","TRDV3"),
geneEntrezID = c("28526","28522","28521","28520","28519","28518","28517","28516"),
GeneSet = rep("TCRD", 8)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "TCRD.csv", row.names = FALSE)
#39. T regs
data <- data.frame(
geneSymbol = c("FOXP3","IKZF2"),
geneEntrezID = c("50943","22807"),
GeneSet = rep("T regs", 2)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "T_regs.csv", row.names = FALSE)
#40. SNOR low DOWN
data <- data.frame(
geneSymbol = c("RNU4ATAC","SNORA11","SNORA16A","SNORA23","SNORA38B","SNORA73A","SNORA73B"),
geneEntrezID = c("100151683","677799","692073","677808","100124536","6080","26768"),
GeneSet = rep("SNOR low DOWN", 7)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "SNOR_low_DOWN.csv", row.names = FALSE)
#--
#41. Monocytes
data <- data.frame(
geneSymbol = c("ACE","ADAM8","ADAMDEC1","ADGRE1","ADGRE2","APOBEC3B","APOBEC3G","APOBR","ART4","C1QA","C1QC","C2","C4A","C4B","C4BPA","C4BPB","C5","C6","C8A","C9","CCL17","CCL18","CCL22","CCL28","CCL7","CCL8","CD14","CD163","CD209","CD300C","CD300E","CD5L","CD80","CFB","CFD","CFP","CHI3L1","CHIT1","CLEC12A","CLEC12B","CLEC4D","CLEC4E","CLEC5A","CLEC7A","CLEC9A","CSF1R","CXCL1","CXCL10","CXCL11","CXCL13","CXCL8","CXCL9","CYBB","F12","FCGR3B","FFAR2","HMMR","HVCN1","IGSF6","IL10RA","IL12A","IL12B","IL1RAP","IL20","IL23A","IL27","IL31RA","LAMP3","LGALS12","LGALS4","LGALS9","LGALS9B","LGALS9C","LILRA2","LILRA5","LILRA6","LILRB5","LMNB1","LY86","LYZ","MARCO","MEGF10","MERTK","MFGE8","MPEG1","MRC1","MS4A4A","MSR1","NTSR1","OCM","OLR1","OSCAR","OTOF","PDCD1LG2","PILRA","PLA2G2D","PLA2G5","PYHIN1","S100A8","S100A9","S1PR5","SCARB1","SCARF2","SECTM1","SEMA4A","SERPINB9","SERPING1","SIGLEC1","SIGLEC14","SIGLEC5","SIGLEC7","SLC11A1","SLITRK4","SMPDL3B","SPIC","STAB2","STAP2","TEK","TGM2","TIMD4","TLR2","TLR8","TNF","TNFAIP8L2","TNFRSF1B","TNIP3","TULP1","UBD","VENTX","VSTM1"),
geneEntrezID = c("1636","101","27299","2015","30817","9582","60489","55911","420","712","714","717","720","721","722","725","727","729","731","735","6361","6362","6367","56477","6354","6355","929","9332","30835","10871","342510","922","941","629","1675","5199","1116","1118","160364","387837","338339","26253","23601","64581","283420","1436","2919","3627","6373","10563","3576","4283","1536","2161","2215","2867","3161","84329","10261","3587","3592","3593","3556","50604","51561","246778","133396","27074","85329","3960","3965","284194","654346","11027","353514","79168","10990","4001","9450","4069","8685","84466","10461","4240","219972","4360","51338","4481","4923","654231","4973","126014","9381","80380","29992","26279","5322","149628","6279","6280","53637","949","91179","6398","64218","5272","710","6614","100049587","8778","27036","6556","139065","27293","121599","55576","55620","7010","7052","91937","7097","51311","7124","79626","7133","79931","7287","10537","27287","284415"),
GeneSet = rep("Monocytes", 130)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Monocytes.csv", row.names = FALSE)
#42. Myeloid cells
data <- data.frame(
geneSymbol = c("ADGRE3","AIF1","AOAH","APOC1","BMX","C1QB","CD101","CD300LF","CD33","CD68","CLEC10A","CLEC16A","CLEC1A","CLEC2B","CLEC4A","CLEC4G","CLEC6A","CSF2RA","CSF2RB","CSF3R","CST3","CYBA","FCER1A","FCER1G","FCGR1A","FCGR1B","FCGR2A","FCGR2B","FCGR2C","FCGR3A","FGR","FLT3","FOLR2","IFI30","IFNL1","IFNL2","IFNL3","IL18","IL1A","IL1B","IL1F10","IL1RN","IL26","IL37","ITGAX","LILRA1","LILRA3","LILRB1","LILRB2","LILRB3","LILRB4","LYVE1","MEFV","MNDA","MS4A6A","MS4A7","NLRP12","NLRP3","NOD2","PECAM1","PLEK","PRAM1","RNASE3","RNASE6","RNASE7","SIGLEC10","SKAP2","SLAMF8","SLPI","SPI1","TNFSF13B","TNFSF14","TREM1","TREML2","TREML4","TWIST1","TYROBP","UNC93B1","VSIG4"),
geneEntrezID = c("84658","199","313","341","660","713","9398","146722","945","968","10462","23274","51267","9976","50856","339390","93978","1438","1439","1441","1471","1535","2205","2207","2209","2210","2212","2213","9103","2214","2268","2322","2350","10437","282618","282616","282617","3606","3552","3553","84639","3557","55801","27178","3687","11024","11026","10859","10288","11025","11006","10894","4210","4332","64231","58475","91662","114548","64127","5175","5341","84106","6037","6039","84659","89790","8935","56833","6590","6688","10673","8740","54210","79865","285852","7291","7305","81622","11326"),
GeneSet = rep("Myeloid cells", 79)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Myeloid_cells.csv", row.names = FALSE)
#43. Neutrophils
data <- data.frame(
geneSymbol = c("ABHD3","ARG1","BPI","CAMP","CD177","CD83","CRISP3","DEFA1","DEFA1B","DEFA3","DEFB103A","DEFB103B","DEFB106B","DEFB136","DEFB4A","FUT4","LY6E","MMP8","OLFM4","OR1J2","PGLYRP1","PRTN3","S100A6"),
geneEntrezID = c("171586","383","671","820","57126","9308","10321","1667","728358","1668","414325","55894","503841","613210","1673","2526","4061","4317","10562","26740","8993","5657","6277"),
GeneSet = rep("Neutrophils", 23)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Neutrophils.csv", row.names = FALSE)
#44. Neutrophils_
data <- data.frame(
geneSymbol = c("EMR2","C5AR2","PLEKHG3","DPEP2","PADI4","FAM212B","TREML2","REPS2","MAK","STEAP4","PGLYRP1","MXD1","MEFV","BTNL8","CREB5","ALOX5","BST1","CEACAM3","VNN3","LILRA2","HSPA6","NFE2","HAL","FFAR2","MMP25","QPCT","CDA","P2RY13","CHST15","TNFRSF10C","FPR2","MGAM","APOBEC3A","TLR2","CXCR1","FAM65B","LST1","TREM1","CSF3R","C5AR1","SELL","AQP9","CXCR2","VNN2","MNDA","FPR1","FCGR3B"),
GeneSet = rep("Neutrophils_", 47)
)
data$geneSymbol <- sub("\\..*", "", data$geneSymbol)
# Fetch ENSEMBL IDs for your gene symbols
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneSymbol,
keytype="SYMBOL",
columns=c("ENSEMBL", "ENTREZID"))
# Join the original data with the fetched IDs
result <- left_join(data, ensembl_ids, by = c("geneSymbol"="SYMBOL"))
# Arrange columns as desired
sorted_result <- result[, c("geneSymbol", "ENTREZID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Neutrophils_.csv", row.names = FALSE)
#45. Inflammatory_neutrophils
data <- data.frame(
geneSymbol = c("CD177.1","ZDHHC19.1","PLAC8.1","IFI6.2","MT2A.2","SERPING1.2","RSAD2.2","GBP1.2","ISG15.2","LY6E.2","S100A12.2","GBP5.2","XAF1.2","IFI44L.2","IFIT3.2","IFITM3.2","SELL.2","TRIM22.2","EPSTI1.2","FCER1G.2","IFI44.2","CST7.1","OAS1.2","TNFSF13B.2","SLFN5","IFIT2.2","MX1.2","PLSCR1.2","MMP9.2","LAP3","OAS2.2","IFIT1.2","TAP1.2","SAMD9L.2","HIST1H2AC.1","APOL6.2","OASL.1","DDX58.1","WSB1.1","RPL28.1","IL1RN.2","MCEMP1.1","HERC5.1","IRF7.2","CKAP4.1","UBE2L6.1","RNF213.2","GBP2.2","CLEC4D.1","LILRA6.1","SHISA5.2","PHF11.1","IFI16.2","OAS3.1","PIM1.1","SERPINB1.1","GYG1.1","IFITM1.1","PSTPIP2","TMSB10.1","GBP4","NFKBIA.2","EIF2AK2.1","FFAR2.2","PARP9.1","NT5C3A","TNFSF10.2","MYL12A.1","PARP14.1","DDX60","DDX60L.2","STAT1.1","XRN1","SAMD9.2","SNX3","HIST1H2BD","PGD.1","FCGR1A","JUN","CD44","PLP2.1","CARD16.2","LIMK2.2","CYSTM1.1","HMGB2.1","IFIH1.2","C1orf162","KLF4","STAT2","ZBP1","ALPL.1","GSTK1","SP110.2","ANXA1","ANXA3.1","METTL9","PML","NUCB1","CEACAM1","SECTM1","PSMB9.1","SAT1","RNF10.1","MAPK14.1","LILRA5","C3AR1","ZCCHC2","SAMHD1","LGALS9","CR1","C4orf3","IRF1.1","CD63","GRINA","TXN.1","MX2.1","GAPDH.1","RBCK1","NBN.2","NMI.1","CAST","HIST2H2BE","NTNG2","SP100.1","CASP1.1","TNFAIP6","PLEK.1","LMNB1","NFIL3","APOL2","BST1","NUB1","PIK3AP1","CCR1.2","ALOX5AP.1","EMB","ISG20","TMEM123.1","ADAR","GIMAP4","SPTLC2","SAMSN1.1","SPI1","GRN.1","APOBEC3A","GLRX","CD53.1","TRIM38","CD82","SH3GLB1","VIM.1","ADM.1","CASP4.1","S100A6.1","RAC2.1","BAZ1A","ADD3","ITGAM","LY96.2","MSRB1.1","DYSF.1","MOB1A","TPM3.1","FGR","ACSL1","IL2RG.1","CDKN2D","FYB1.1","CLEC4E.1","HLA-F","LILRB3","RBMS1","PLBD1","FLOT1","GNG5","PTEN.1","PROK2.1","UBE2J1","CD37.1","KCNJ15.1","BRI3.1","HIF1A","PRR13.1","LRG1","MAX","RHOG","NFE2","STXBP2","B4GALT5","CAPZA1","SERPINA1","ZYX","RGS19","FKBP5","GCA.1","FKBP1A","MTPN","VNN2","AC245128.3","CD55","CFL1.1"), # shortened for clarity
GeneSet = rep("Inflammatory neutrophils", 201)
)
data$geneSymbol <- sub("\\..*", "", data$geneSymbol)
# Fetch ENSEMBL IDs for your gene symbols
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneSymbol,
keytype="SYMBOL",
columns=c("ENSEMBL", "ENTREZID"))
# Join the original data with the fetched IDs
result <- left_join(data, ensembl_ids, by = c("geneSymbol"="SYMBOL"))
# Arrange columns as desired
sorted_result <- result[, c("geneSymbol", "ENTREZID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Inflammatory_neutrophils.csv", row.names = FALSE)
#46. Suppressive_neutrophils
data <- data.frame(
geneSymbol = c("LY6E","XAF1","RSAD2","ISG15","IFI44L","IFITM3","MT2A","IFIT3","EPSTI1","IFIT1","IFI6","IFIT2","MX1","GBP5","PLSCR1","SELL","SERPING1","SHISA5","TRIM22","GBP1","IFI44","IRF7","FFAR2","OAS1","OAS2","IL1RN","IFI16","CCR1","SP110","APOL6","NFKBIA","TNFSF10","FCER1G","IFIH1","TNFSF13B","SAMD9","SAMD9L","DDX60L","TAP1","NBN","RNF213","CARD16","GBP2","LY96","CLEC2B","LIMK2"),
GeneSet = rep("Suppressive neutrophils", 46)
)
data$geneSymbol <- sub("\\..*", "", data$geneSymbol)
# Fetch ENSEMBL IDs for your gene symbols
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneSymbol,
keytype="SYMBOL",
columns=c("ENSEMBL", "ENTREZID"))
# Join the original data with the fetched IDs
result <- left_join(data, ensembl_ids, by = c("geneSymbol"="SYMBOL"))
# Arrange columns as desired
sorted_result <- result[, c("geneSymbol", "ENTREZID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Suppressive_neutrophils.csv", row.names = FALSE)
#47. Apoptosis
data <- data.frame(
geneSymbol = c("AIFM1","APAF1","BAD","BAK1","BAX","BCL2L11","BID","CASP10","CASP2","CASP3","CASP6","CASP7","CASP8","CASP9","DIABLO","ENDOG","FAS","FASLG","HTRA2","TNFRSF1A","TP53"),
geneEntrezID = c("9131","317","572","578","581","10018","637","843","835","836","839","840","841","842","56616","2021","355","356","27429","7132","7157"),
GeneSet = rep("Apoptosis", 21)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "Apoptosis.csv", row.names = FALSE)
#48. NFkB complex
data <- data.frame(
geneSymbol = c("IKBKB","IKBKG","NFKB1","NFKB2","RELA","RELB","REL"),
geneEntrezID = c("3551","8517","4790","4791","5970","5971","5966"),
GeneSet = rep("NFkB complex", 7)
)
ensembl_ids <- AnnotationDbi::select(org.Hs.eg.db,
keys=data$geneEntrezID,
keytype="ENTREZID",
columns="ENSEMBL")
result <- left_join(data, ensembl_ids, by = c("geneEntrezID"="ENTREZID"))
sorted_result <- result[, c("geneSymbol", "geneEntrezID", "ENSEMBL", "GeneSet")]
write.csv(sorted_result, file = "NFkB_complex.csv", row.names = FALSE)
#~/Tools/csv2xls-0.4/csv_to_xls.py Alt._complement.csv Anergic_or_act._T_cells.csv Anti-inflammation.csv B_cells.csv CD40_activated.csv CD8T-NK-NKT.csv Cell_cycle.csv Classical_complement.csv Cyt._act._T_cells.csv Dendritic_cells.csv Erythrocytes.csv Granulocytes.csv IFN.csv IG_chains.csv IL-1_cytokines.csv IL-6R_complex.csv Inflammasome.csv LDG.csv Lectin_complement.csv MHC_II.csv Monocytes.csv Monocytes_40.csv Monocyte_cell_surface.csv Monocyte_secreted.csv Myeloid_cells.csv Neutrophils.csv NK_cells.csv NLRP3_inflammasome.csv pDC.csv Plasma_cells.csv Platelets.csv Pro-inflam._IL-1.csv SNOR_low_DOWN.csv SNOR_low_UP.csv TCRA.csv TCRB.csv TCRD.csv TCRG.csv TNF.csv T_activated.csv T_cells.csv T_regs.csv Unfolded_protein.csv Neutrophils_.csv Inflammatory_neutrophils.csv Suppressive_neutrophils.csv Apoptosis.csv NFkB_complex.csv -d',' -o Signatures.xls
#---------------------------------------------------------------------
#---- 2. Prepare gene expression matrix: calculate DESeq2 results ----
setwd("/home/jhuang/DATA/Data_Susanne_Carotis_RNASeq/results/featureCounts_2023")
library("AnnotationDbi")
library("clusterProfiler")
library("ReactomePA")
#BiocManager::install("org.Hs.eg.db")
library("org.Hs.eg.db")
library(DESeq2)
library(gplots)
d.raw<- read.delim2("merged_gene_counts.txt",sep="\t", header=TRUE, row.names=1)
colnames(d.raw)<-c("gene_name", "leer_mock_2h_r2", "Ace2_mock_2h_r2", "leer_inf_24h_r1", "Ace2_inf_2h_r1", "leer_inf_24h_r2", "leer_inf_2h_r1", "leer_mock_2h_r1", "leer_inf_2h_r2", "Ace2_inf_2h_r2", "Ace2_mock_2h_r1", "Ace2_inf_24h_r2", "Ace2_inf_24h_r1")
col_order <- c("gene_name", "leer_mock_2h_r1","leer_mock_2h_r2","leer_inf_2h_r1","leer_inf_2h_r2","leer_inf_24h_r1","leer_inf_24h_r2","Ace2_mock_2h_r1","Ace2_mock_2h_r2","Ace2_inf_2h_r1","Ace2_inf_2h_r2","Ace2_inf_24h_r1","Ace2_inf_24h_r2")
reordered.raw <- d.raw[,col_order]
reordered.raw$gene_name <- NULL
#d <- d.raw[rowSums(reordered.raw>3)>2,]
condition = as.factor(c("leer_mock_2h","leer_mock_2h","leer_inf_2h","leer_inf_2h","leer_inf_24h","leer_inf_24h","Ace2_mock_2h","Ace2_mock_2h","Ace2_inf_2h","Ace2_inf_2h","Ace2_inf_24h","Ace2_inf_24h"))
ids = as.factor(c("leer_mock_2h_r1","leer_mock_2h_r2","leer_inf_2h_r1","leer_inf_2h_r2","leer_inf_24h_r1","leer_inf_24h_r2","Ace2_mock_2h_r1","Ace2_mock_2h_r2","Ace2_inf_2h_r1","Ace2_inf_2h_r2","Ace2_inf_24h_r1","Ace2_inf_24h_r2"))
#cData = data.frame(row.names=colnames(reordered.raw), condition=condition, batch=batch, ids=ids)
#dds<-DESeqDataSetFromMatrix(countData=reordered.raw, colData=cData, design=~batch+condition)
cData = data.frame(row.names=colnames(reordered.raw), condition=condition, ids=ids)
dds<-DESeqDataSetFromMatrix(countData=reordered.raw, colData=cData, design=~condition)
#----more detailed and specific with the following code!----
dds$condition <- relevel(dds$condition, "Ace2_mock_2h")
dds = DESeq(dds, betaPrior=FALSE) # betaPrior default value is FALSE
resultsNames(dds)
#--------------------------------------
#---- 3. draw violin on signatures ----
library(GSVA)
library(ggplot2)
#install.packages("readxl")
library(readxl)
# Path to the Excel file
file_path <- "Signatures.xls"
#example of a signature:
#geneSymbol geneEntrezID ENSEMBL GeneSet
#CD160 11126 ENSG00000117281 Anergic or act. T cells
#CD244 51744 ENSG00000122223 Anergic or act. T cells
#CTLA4 1493 ENSG00000163599 Anergic or act. T cells
#HAVCR2 84868 ENSG00000135077 Anergic or act. T cells
#ICOS 29851 ENSG00000163600 Anergic or act. T cells
#KLRG1 10219 ENSG00000139187 Anergic or act. T cells
#LAG3 3902 ENSG00000089692 Anergic or act. T cells
#PDCD1 5133 ENSG00000188389 Anergic or act. T cells
#PDCD1 5133 ENSG00000276977 Anergic or act. T cells
# Get the names of the sheets
sheet_names <- excel_sheets(file_path)
# Initialize an empty list to hold gene sets
geneSets <- list()
# Loop over each sheet, extract the ENSEMBL IDs, and add to the list
for (sheet in sheet_names) {
# Read the sheet
data <- read_excel(file_path, sheet = sheet)
# Process the GeneSet names (replacing spaces with underscores, for example)
gene_set_name <- gsub(" ", "_", unique(data$GeneSet)[1])
# Add ENSEMBL IDs to the list
geneSets[[gene_set_name]] <- as.character(data$ENSEMBL)
}
# Print the result to check
print(geneSets)
# 0. for Nanostring, the GSVA input requires a gene expression matrix 'exprs' where rows are genes and columns are samples.
#exprs <- exprs(filtered_or_neg_target_m666Data)
# 0. for RNAseq, the GSVA input requires a gene expression matrix where rows are genes and columns are samples.
exprs <- counts(dds, normalized=TRUE)
# 1. Compute GSVA scores:
library(GSVA)
gsva_scores <- gsva(exprs, geneSets, method="gsva")
# 2. Convert to data.frame for ggplot:
gsva_df <- as.data.frame(t(gsva_scores))
# 3. Add conditions to gsva_df:
gsva_df$Condition <- dds$condition
# 4. Filter the gsva_df to retain only the desired conditions:
#group 1 vs. group 3 in the nanostring data
gsva_df_filtered <- gsva_df[gsva_df$Condition %in% c("Ace2_mock_2h", "Ace2_inf_24h"), ]
# 5. Define a function to plot violin plots:
# Update the condition levels in gsva_df_filtered to ensure the desired order on x-axis:
gsva_df_filtered$Condition <- gsub("Ace2_mock_2h", "mock", gsva_df_filtered$Condition)
gsva_df_filtered$Condition <- gsub("Ace2_inf_24h", "infection", gsva_df_filtered$Condition)
gsva_df_filtered$Condition <- factor(gsva_df_filtered$Condition, levels = c("mock", "infection"))
plot_violin <- function(data, gene_name) {
# Calculate the t-test p-value for the two conditions
condition1_data <- data[data$Condition == "mock", gene_name]
condition2_data <- data[data$Condition == "infection", gene_name]
p_value <- t.test(condition1_data, condition2_data)$p.value
# Convert p-value to annotation
p_annotation <- ifelse(p_value < 0.01, "**", ifelse(p_value < 0.05, "*", ""))
rounded_p_value <- paste0("p = ", round(p_value, 2))
plot_title <- gsub("_", " ", gene_name)
p <- ggplot(data, aes(x=Condition, y=!!sym(gene_name))) +
geom_violin(linewidth=1.2) +
labs(title=plot_title, y="GSVA Score") +
ylim(-1, 1) +
theme_light() +
theme(
axis.title.x = element_text(size=12),
axis.title.y = element_text(size=12),
axis.text.x = element_text(size=10),
axis.text.y = element_text(size=10),
plot.title = element_text(size=12, hjust=0.5)
)
# Add p-value annotation to the plot
p <- p + annotate("text", x=1.5, y=0.9, label=paste0(p_annotation, " ", rounded_p_value), size=5, hjust=0.5)
return(p)
}
# 6. Generate the list of plots:
#genes <- colnames(gsva_df_filtered)[!colnames(gsva_df_filtered) %in% "Condition"]
#plots_list <- lapply(genes, function(gene) plot_violin(gsva_df_filtered, gene))
# 6. Generate the list of plots in a predefined order:
desired_order <- c("Platelets","Granulocytes","LDG","pDC","Anti-inflammation", "Pro-inflam._IL-1","Dendritic_cells","MHC_II","Alt._complement","TNF", "NLRP3_inflammasome","Unfolded_protein","B_cells","Monocyte_cell_surface","Inflammasome", "Monocyte_secreted","IL-1_cytokines","SNOR_low_UP","CD40_activated","Lectin_complement", "Classical_complement","Cell_cycle","Plasma_cells","IG_chains","Erythrocytes", "IL-6R_complex","IFN","TCRB","TCRA","Cyt._act._T_cells", "TCRG","T_cells","CD8T-NK-NKT","Anergic_or_act._T_cells","T_activated", "NK_cells","TCRD","T_regs","SNOR_low_DOWN","Monocytes", "Myeloid_cells","Neutrophils")
genes <- colnames(gsva_df_filtered)[!colnames(gsva_df_filtered) %in% "Condition"]
genes <- genes[match(desired_order, genes)]
plots_list <- lapply(genes, function(gene) plot_violin(gsva_df_filtered, gene))
# 7. Pad the list of plots:
remaining_plots <- 6 - (length(plots_list) %% 6)
if (remaining_plots != 6) {
plots_list <- c(plots_list, rep(list(NULL), remaining_plots))
}
# 8. Create the plots and arrange them in a grid:
library(gridExtra)
plots_matrix <- matrix(plots_list, ncol=6, byrow=T)
#do.call("grid.arrange", c(plots_matrix, list(ncol=6)))
# 9. Save the plots to a PNG:
png("All_Violin_Plots_RNAseq.png", width=1000, height=1000)
do.call("grid.arrange", c(plots_matrix, list(ncol=6)))
dev.off()
# ------------------------ Heatmap Presentation --------------------
#-- NanoString GSVA scores --
exprs <- exprs(target_m666Data)
#exprs <- exprs(filtered_or_neg_target_m666Data)
# 1. Compute GSVA scores:
gsva_scores <- gsva(exprs, geneSets, method="gsva")
# 2. Convert to data.frame for ggplot:
gsva_df <- as.data.frame(t(gsva_scores))
# 3. Add conditions to gsva_df:
identical(rownames(pData(target_m666Data)), rownames(gsva_df))
gsva_df$Condition <- pData(target_m666Data)$Grp
gsva_df$SampleID <- pData(target_m666Data)$SampleID
# 4. Filter the gsva_df to retain only the desired conditions:
gsva_df_filtered <- gsva_df[gsva_df$Condition %in% c("1", "3"), ]
# 5. Define a function to plot violin plots:
# Update the condition levels in gsva_df_filtered to ensure the desired order on x-axis:
gsva_df_filtered$Condition <- gsub("1", "Group1", gsva_df_filtered$Condition)
gsva_df_filtered$Condition <- gsub("3", "Group3", gsva_df_filtered$Condition)
gsva_df_filtered$Condition <- factor(gsva_df_filtered$Condition, levels = c("Group1", "Group3"))
# Filter the data for "Group1" samples
group1_data <- gsva_df_filtered[gsva_df_filtered$Condition == "Group1", genes]
# Set the median values for each column in the data.frame
# Calculate median values for each column
group1_medians <- apply(group1_data, 2, median)
# 3. Add conditions to gsva_df:
identical(rownames(pData(target_m666Data)), rownames(gsva_df))
gsva_df$Condition <- pData(target_m666Data)$Group
#identical(rownames(gsva_df_filtered), rownames(pData(target_m666Data)) )
gsva_df$SampleID <- pData(target_m666Data)$SampleID
# 4. Filter the gsva_df to retain only the desired conditions:
#group 1 vs. group 3 in the nanostring data
gsva_df_filtered <- gsva_df[gsva_df$Condition %in% c("1a", "1b", "3"), ]
# 5. Define a function to plot violin plots:
# Update the condition levels in gsva_df_filtered to ensure the desired order on x-axis:
gsva_df_filtered$Condition <- gsub("1a", "Group1a", gsva_df_filtered$Condition)
gsva_df_filtered$Condition <- gsub("1b", "Group1b", gsva_df_filtered$Condition)
gsva_df_filtered$Condition <- gsub("3", "Group3", gsva_df_filtered$Condition)
gsva_df_filtered$Condition <- factor(gsva_df_filtered$Condition, levels = c("Group1a", "Group1b", "Group3"))
# Filter the data for "Group1a" samples
group1a_data <- gsva_df_filtered[gsva_df_filtered$Condition == "Group1a", genes]
group1a_medians <- apply(group1a_data, 2, median)
# Filter the data for "Group1b" samples
group1b_data <- gsva_df_filtered[gsva_df_filtered$Condition == "Group1b", genes]
group1b_medians <- apply(group1b_data, 2, median)
# Filter the data for "Group3" samples
group3_data <- gsva_df_filtered[gsva_df_filtered$Condition == "Group3", genes]
group3_medians <- apply(group3_data, 2, median)
#-- RNAseq GSVA scores --
exprs <- counts(dds, normalized=TRUE)
# 1. Compute GSVA scores:
gsva_scores <- gsva(exprs, geneSets, method="gsva")
# 2. Convert to data.frame for ggplot:
gsva_df <- as.data.frame(t(gsva_scores))
# 3. Add conditions to gsva_df:
gsva_df$Condition <- dds$condition
# 4. Filter the gsva_df to retain only the desired conditions:
#group 1 vs. group 3 in the nanostring data
gsva_df_filtered <- gsva_df[gsva_df$Condition %in% c("Ace2_mock_2h", "Ace2_inf_24h"), ]
# 5. Define a function to plot violin plots:
# Update the condition levels in gsva_df_filtered to ensure the desired order on x-axis:
gsva_df_filtered$Condition <- gsub("Ace2_mock_2h", "mock", gsva_df_filtered$Condition)
gsva_df_filtered$Condition <- gsub("Ace2_inf_24h", "infection", gsva_df_filtered$Condition)
gsva_df_filtered$Condition <- factor(gsva_df_filtered$Condition, levels = c("mock", "infection"))
# Filter the data for "mock" samples
mock_data <- gsva_df_filtered[gsva_df_filtered$Condition == "mock", genes]
mock_medians <- apply(mock_data, 2, median)
# Filter the data for "infection" samples
infection_data <- gsva_df_filtered[gsva_df_filtered$Condition == "infection", genes]
infection_medians <- apply(infection_data, 2, median)
# Create a new data frame with the middle values for both groups
heatmap_data_rnaseq <- data.frame(mock = mock_medians, infection = infection_medians)
# Transpose the data matrix to switch rows and columns
#heatmap_data <- t(heatmap_data)
# Convert the data frame to a numeric matrix
heatmap_matrix <- as.matrix(heatmap_data)
# Specify heatmap colors
color_scheme <- colorRampPalette(c("blue", "white", "red"))(50)
#TODO: adjust the color, so that it is not so dark and light!!!!, add RNAseq data for mock and infection!!
# Create the heatmap without hierarchical clustering
library(gplots)
png("Heatmap.png", width=1000, height=1000)
heatmap.2(
heatmap_matrix,
Colv = FALSE, # Turn off column dendrogram
Rowv = FALSE, # Turn off row dendrogram
trace = "none", # Turn off row and column dendrograms
scale = "row", # Scale the rows
col = color_scheme,
main = "GSVA Heatmap", # Title of the heatmap
key = TRUE, # Show color key
key.title = "GSVA Score", # Color key title
key.xlab = NULL, # Remove x-axis label from color key
density.info = "none", # Remove density plot
cexRow = 1.2, # Increase font size of row names
cexCol = 1.2, # Increase font size of column names
srtCol = 40, keysize = 0.72, margins = c(5, 14)
)
dev.off()
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