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AS_GO.R
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AS_GO.R
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#### AS GO
library(org.Hs.eg.db)##### data base target to human-geneIDs
library(AnnotationDbi)
library(DOSE)
library(GO.db)
library(topGO)
library(GSEABase)
library(clusterProfiler)
#background <- as.character(read.table("/Users/tangchao/CloudStation/tangchao/project/UCB/AS_GO/Background_for_GO.txt", header = F, stringsAsFactors = F)[,1])
background <- as.character(read.table("/mnt/data5/BGI/UCB/tangchao/DSU2/Document/Background_for_GO.txt", header = F, stringsAsFactors = F)[,1])
Cell_type <- read.table("/mnt/data5/BGI/UCB/ExpMat_NewID/Cell_type.txt", header = F, row.names = 1, sep = "\t", stringsAsFactors=F)
colnames(Cell_type) <- "CellType"
Cell_type <- data.frame(CellType = Cell_type[order(Cell_type),], row.names = row.names(Cell_type)[order(Cell_type)])
Cell_type$Individual <- substr(row.names(Cell_type), 1, 4)
#### SE =========================================================================================================================================
load("/mnt/data5/BGI/UCB/tangchao/DSU2/SE/SE_psi_new.RData")
PSI <- SE_psi[, row.names(Cell_type)]
row.names(PSI) <- SE_psi$loci
rs <- rowSums(!is.na(PSI))
summary(rs)
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 0.0 17.0 76.0 256.3 273.8 3039.0
sum(rs==0)
#[1] 53
sum(rs==1)
#[1] 513
PSI <- PSI[rs!=0, ]
rs <- rowSums(!is.na(PSI) & PSI != 0 & PSI != 1)
# summary(rs)
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 0.00 0.00 1.00 12.62 3.00 2600.00
sum(rs==0)
# [1] 7802
sum(rs==1)
# [1] 3404
table(SE_psi[SE_psi$loci %in% names(rs)[rs>=1], "SE_type"])
# exon-skipping_exactly novel_exon-skipping Other
# 5272 1859 2684
table(SE_psi[SE_psi$loci %in% names(rs)[rs==0], "SE_type"])
# exon-skipping_exactly novel_exon-skipping Other
# 5088 1529 1185
all_SE_gene <- unique(SE_psi[SE_psi$loci %in% row.names(PSI), "gene_id"])
length(all_SE_gene)
#[1] 5890
SE_gene_0 <- unique(SE_psi[SE_psi$loci %in% names(rs)[rs==0], "gene_id"])
SE_gene_1 <- unique(SE_psi[SE_psi$loci %in% names(rs)[rs>=1], "gene_id"])
length(SE_gene_0)
#[1] 3686
length(SE_gene_1)
#[1] 3045
#### GO
SE_BP_ego <- enrichGO(gene = all_SE_gene,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
SE_MF_ego <- enrichGO(gene = all_SE_gene,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "MF",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
SE_CC_ego <- enrichGO(gene = all_SE_gene,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "CC",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/all_SE_gene_GO.pdf",height = 10,width = 15)
print(dotplot(SE_BP_ego,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(SE_MF_ego,showCategory = 10,font.size = 16,title = "MF"))
print(dotplot(SE_CC_ego,showCategory = 10,font.size = 16,title = "CC"))
suppressMessages(plotGOgraph(SE_BP_ego,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(SE_MF_ego,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(SE_CC_ego,firstSigNodes = 15, useInfo = "all"))
enrichMap(SE_BP_ego,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(SE_MF_ego,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(SE_CC_ego,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
SE_BP_ego_0 <- enrichGO(gene = SE_gene_0,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
SE_MF_ego_0 <- enrichGO(gene = SE_gene_0,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "MF",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
SE_CC_ego_0 <- enrichGO(gene = SE_gene_0,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "CC",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Pseudo_SE_gene_GO.pdf",height = 10,width = 15)
print(dotplot(SE_BP_ego_0,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(SE_MF_ego_0,showCategory = 10,font.size = 16,title = "MF"))
print(dotplot(SE_CC_ego_0,showCategory = 10,font.size = 16,title = "CC"))
suppressMessages(plotGOgraph(SE_BP_ego_0,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(SE_MF_ego_0,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(SE_CC_ego_0,firstSigNodes = 15, useInfo = "all"))
enrichMap(SE_BP_ego_0,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(SE_MF_ego_0,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(SE_CC_ego_0,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
SE_BP_ego_1 <- enrichGO(gene = SE_gene_1,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
SE_MF_ego_1 <- enrichGO(gene = SE_gene_1,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "MF",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
SE_CC_ego_1 <- enrichGO(gene = SE_gene_1,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "CC",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Real_SE_gene_GO.pdf",height = 10,width = 15)
print(dotplot(SE_BP_ego_1,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(SE_MF_ego_1,showCategory = 10,font.size = 16,title = "MF"))
print(dotplot(SE_CC_ego_1,showCategory = 10,font.size = 16,title = "CC"))
suppressMessages(plotGOgraph(SE_BP_ego_1,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(SE_MF_ego_1,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(SE_CC_ego_1,firstSigNodes = 15, useInfo = "all"))
enrichMap(SE_BP_ego_1,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(SE_MF_ego_1,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(SE_CC_ego_1,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
background_enid <- as.character(na.omit(mapIds(org.Hs.eg.db, keys = background, column = "ENTREZID", keytype = "ENSEMBL")))
all_SE_gene_enid <- as.character(na.omit(mapIds(org.Hs.eg.db, keys = all_SE_gene, column = "ENTREZID", keytype = "ENSEMBL")))
all_SE_gene_enid <- all_SE_gene_enid[!is.na(all_SE_gene_enid)]
keytypes(org.Hs.eg.db)
background_enid <- bitr(background, fromType="ENSEMBL", toType="ENTREZID", OrgDb="org.Hs.eg.db")$ENTREZID
all_SE_gene_enid <- bitr(all_SE_gene, fromType="ENSEMBL", toType="ENTREZID", OrgDb="org.Hs.eg.db")$ENTREZID
SE_gene_0_enid <- bitr(SE_gene_0, fromType="ENSEMBL", toType="ENTREZID", OrgDb="org.Hs.eg.db")$ENTREZID
SE_gene_1_enid <- bitr(SE_gene_1, fromType="ENSEMBL", toType="ENTREZID", OrgDb="org.Hs.eg.db")$ENTREZID
SE_KEGG <- enrichKEGG(gene = all_SE_gene_enid,
organism = 'hsa',
universe = background_enid,
pvalueCutoff = 0.05)
head(SE_KEGG)
SE_0_KEGG <- enrichKEGG(gene = SE_gene_0_enid,
organism = 'hsa',
universe = background_enid,
pvalueCutoff = 0.05)
SE_1_KEGG <- enrichKEGG(gene = SE_gene_1_enid,
organism = 'hsa',
universe = background_enid,
pvalueCutoff = 0.05)
SE_mkk <- enrichMKEGG(gene = all_SE_gene_enid,
organism = 'hsa',
universe = background_enid)
SE_0_mkk <- enrichMKEGG(gene = SE_gene_0_enid,
organism = 'hsa',
universe = background_enid)
SE_1_mkk <- enrichMKEGG(gene = SE_gene_1_enid,
organism = 'hsa',
universe = background_enid)
head(SE_mkk)
SE_do <- DOSE::enrichDO(gene = all_SE_gene_enid,
ont = "DO",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
#universe = background_enid,
minGSSize = 5,
maxGSSize = 500,
qvalueCutoff = 0.05,
readable = FALSE)
SE_0_do <- DOSE::enrichDO(gene = SE_gene_0_enid,
ont = "DO",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
#universe = background_enid,
minGSSize = 5,
maxGSSize = 500,
qvalueCutoff = 0.05,
readable = FALSE)
SE_1_do <- DOSE::enrichDO(gene = SE_gene_1_enid,
ont = "DO",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
#universe = background_enid,
minGSSize = 5,
maxGSSize = 500,
qvalueCutoff = 0.05,
readable = FALSE)
head(SE_do)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/all_SE_gene_DO.pdf",height = 10,width = 15)
print(dotplot(SE_do,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(SE_do,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Pseudo_SE_gene_DO.pdf",height = 10,width = 15)
print(dotplot(SE_0_do,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(SE_0_do,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Real_SE_gene_DO.pdf",height = 10,width = 15)
print(dotplot(SE_1_do,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(SE_1_do,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
dgn <- enrichDGN(gene = all_SE_gene_enid,
#universe = background_enid,
qvalueCutoff = 0.05,
readable = TRUE)
dgn_0 <- enrichDGN(gene = SE_gene_0_enid,
#universe = background_enid,
qvalueCutoff = 0.05,
readable = TRUE)
dgn_1 <- enrichDGN(gene = SE_gene_1_enid,
#universe = background_enid,
qvalueCutoff = 0.05,
readable = TRUE)
head(dgn)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/all_SE_gene_DGN.pdf",height = 10,width = 15)
print(dotplot(dgn,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(dgn,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Pseudo_SE_gene_DGN.pdf",height = 10,width = 15)
print(dotplot(dgn_0,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(dgn_0,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Real_SE_gene_DGN.pdf",height = 10,width = 15)
print(dotplot(dgn_1,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(dgn_1,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
library(ReactomePA)
SE_Path <- enrichPathway(gene = all_SE_gene_enid,
organism = "human",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
qvalueCutoff = 0.2,
universe = background_enid,
minGSSize = 10,
maxGSSize = 500,
readable = FALSE)
SE_0_Path <- enrichPathway(gene = SE_gene_0_enid,
organism = "human",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
qvalueCutoff = 0.2,
universe = background_enid,
minGSSize = 10,
maxGSSize = 500,
readable = FALSE)
SE_1_Path <- enrichPathway(gene = SE_gene_1_enid,
organism = "human",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
qvalueCutoff = 0.2,
universe = background_enid,
minGSSize = 10,
maxGSSize = 500,
readable = FALSE)
SE_BP_ego_1
SE_1_KEGG
dgn_1
print(dotplot(SE_BP_ego_1,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(SE_1_KEGG,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(dgn_1,showCategory = 10,font.size = 16,title = "BP"))
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/all_SE_gene_KEGG.pdf",height = 10,width = 15)
print(dotplot(SE_KEGG,showCategory = 10,font.size = 16, title = "BP"))
#suppressMessages(plotGOgraph(SE_KEGG,firstSigNodes = 15, useInfo = "all"))
enrichMap(SE_KEGG,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Pseudo_SE_gene_KEGG.pdf",height = 10,width = 15)
print(dotplot(SE_0_KEGG,showCategory = 10,font.size = 16, title = "BP"))
enrichMap(SE_0_KEGG,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Real_SE_gene_KEGG.pdf",height = 10,width = 15)
print(dotplot(SE_1_KEGG,showCategory = 10,font.size = 16, title = "BP"))
enrichMap(SE_1_KEGG,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Real_SE_gene_DGN.pdf",height = 10,width = 15)
print(dotplot(dgn_1,showCategory = 10,font.size = 16, title = "BP"))
#suppressMessages(plotGOgraph(SE_KEGG,firstSigNodes = 15, useInfo = "all"))
enrichMap(dgn_1,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/all_SE_gene_Pathway.pdf",height = 10,width = 15)
print(dotplot(SE_Path,showCategory = 10,font.size = 16, title = "BP"))
#suppressMessages(plotGOgraph(SE_Path,firstSigNodes = 15, useInfo = "all"))
enrichMap(SE_Path,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Pseudo_SE_gene_Pathway.pdf",height = 10,width = 15)
print(dotplot(SE_0_Path,showCategory = 10,font.size = 16, title = "BP"))
enrichMap(SE_0_Path,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/Real_SE_gene_Pathway.pdf",height = 10,width = 15)
print(dotplot(SE_1_Path,showCategory = 10,font.size = 16, title = "BP"))
enrichMap(SE_1_Path,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
CompareGO_BP <- compareCluster(geneCluster = list(All = all_SE_gene, Pseudo = SE_gene_0, Real = SE_gene_1),
universe = background,
fun ="enrichGO",
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
CompareGO_MF <- compareCluster(geneCluster = list(All = all_SE_gene, Pseudo = SE_gene_0, Real = SE_gene_1),
universe = background,
fun ="enrichGO",
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "MF",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
CompareGO_CC <- compareCluster(geneCluster = list(All = all_SE_gene, Pseudo = SE_gene_0, Real = SE_gene_1),
universe = background,
fun ="enrichGO",
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "CC",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/SE_CompareGO.pdf", height = 8, width = 20)
print(dotplot(CompareGO_BP,showCategory = 10,font.size = 16,title = "SE GO BP"))
print(dotplot(CompareGO_MF,showCategory = 10,font.size = 16,title = "SE GO MF"))
print(dotplot(CompareGO_CC,showCategory = 10,font.size = 16,title = "SE GO CC"))
dev.off()
CompareKEGG <- compareCluster(geneCluster = list(All = all_SE_gene_enid, Pseudo = SE_gene_0_enid, Real = SE_gene_1_enid),
universe = background_enid,
fun = "enrichKEGG",
organism = "hsa",
pvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/SE_CompareKEGG.pdf", height = 8, width = 20)
print(dotplot(CompareKEGG,showCategory = 10,font.size = 16,title = "SE KEGG"))
dev.off()
CompareDO <- compareCluster(geneCluster = list(All = all_SE_gene_enid, Pseudo = SE_gene_0_enid, Real = SE_gene_1_enid),
fun = "enrichDO",
ont = "DO",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
#universe = background_enid,
minGSSize = 5,
maxGSSize = 500,
qvalueCutoff = 0.05,
readable = FALSE)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/SE_CompareDO.pdf", height = 8, width = 20)
print(dotplot(CompareDO,showCategory = 10,font.size = 16,title = "SE KEGG"))
dev.off()
library(ReactomePA)
ComparePathway <- compareCluster(geneCluster = list(All = all_SE_gene_enid, Pseudo = SE_gene_0_enid, Real = SE_gene_1_enid),
fun="enrichPathway",
organism = "human",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
qvalueCutoff = 0.2,
universe = background_enid,
minGSSize = 10,
maxGSSize = 500,
readable = FALSE)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/SE/SE_ComparePathway.pdf", height = 8, width = 20)
print(dotplot(ComparePathway,showCategory = 10,font.size = 16,title = "SE Pathway"))
dev.off()
#### A3SS =======================================================================================================================================
load("/mnt/data5/BGI/UCB/tangchao/DSU2/A3SS/A3SS_psi_new.RData")
PSI <- A3SS_psi[, row.names(Cell_type)]
row.names(PSI) <- A3SS_psi$as2
rs <- rowSums(!is.na(PSI))
summary(rs)
PSI <- PSI[rs!=0, ]
rs <- rowSums(!is.na(PSI) & PSI != 0 & PSI != 1)
summary(rs)
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 0.000 0.000 0.000 2.791 1.000 575.000
sum(rs==0)
#[1] 2056
sum(rs==1)
#[1] 470
sum(rs>=1)
#[1] 987
all_A3SS_gene <- unique(A3SS_psi[A3SS_psi$as2 %in% row.names(PSI), "gene_id"])
length(all_A3SS_gene)
#[1] 2412
A3SS_gene_0 <- unique(A3SS_psi[A3SS_psi$as2 %in% names(rs)[rs==0], "gene_id"])
A3SS_gene_1 <- unique(A3SS_psi[A3SS_psi$as2 %in% names(rs)[rs>=1], "gene_id"])
length(A3SS_gene_0)
#[1] 1756
length(A3SS_gene_1)
#[1] 838
#### GO
A3SS_BP_ego <- enrichGO(gene = all_A3SS_gene,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
A3SS_MF_ego <- enrichGO(gene = all_A3SS_gene,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "MF",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
A3SS_CC_ego <- enrichGO(gene = all_A3SS_gene,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "CC",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/all_A3SS_gene_GO.pdf",height = 10,width = 15)
print(dotplot(A3SS_BP_ego,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(A3SS_MF_ego,showCategory = 10,font.size = 16,title = "MF"))
print(dotplot(A3SS_CC_ego,showCategory = 10,font.size = 16,title = "CC"))
suppressMessages(plotGOgraph(A3SS_BP_ego,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(A3SS_MF_ego,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(A3SS_CC_ego,firstSigNodes = 15, useInfo = "all"))
enrichMap(A3SS_BP_ego,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(A3SS_MF_ego,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(A3SS_CC_ego,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
A3SS_BP_ego_0 <- enrichGO(gene = A3SS_gene_0,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
A3SS_MF_ego_0 <- enrichGO(gene = A3SS_gene_0,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "MF",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
A3SS_CC_ego_0 <- enrichGO(gene = A3SS_gene_0,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "CC",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Pseudo_A3SS_gene_GO.pdf",height = 10,width = 15)
print(dotplot(A3SS_BP_ego_0,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(A3SS_MF_ego_0,showCategory = 10,font.size = 16,title = "MF"))
print(dotplot(A3SS_CC_ego_0,showCategory = 10,font.size = 16,title = "CC"))
suppressMessages(plotGOgraph(A3SS_BP_ego_0,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(A3SS_MF_ego_0,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(A3SS_CC_ego_0,firstSigNodes = 15, useInfo = "all"))
enrichMap(A3SS_BP_ego_0,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(A3SS_MF_ego_0,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(A3SS_CC_ego_0,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
A3SS_BP_ego_1 <- enrichGO(gene = A3SS_gene_1,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
A3SS_MF_ego_1 <- enrichGO(gene = A3SS_gene_1,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "MF",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
A3SS_CC_ego_1 <- enrichGO(gene = A3SS_gene_1,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "CC",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Real_A3SS_gene_GO.pdf",height = 10,width = 15)
print(dotplot(A3SS_BP_ego_1,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(A3SS_MF_ego_1,showCategory = 10,font.size = 16,title = "MF"))
print(dotplot(A3SS_CC_ego_1,showCategory = 10,font.size = 16,title = "CC"))
suppressMessages(plotGOgraph(A3SS_BP_ego_1,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(A3SS_MF_ego_1,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(A3SS_CC_ego_1,firstSigNodes = 15, useInfo = "all"))
enrichMap(A3SS_BP_ego_1,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(A3SS_MF_ego_1,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(A3SS_CC_ego_1,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
background_enid <- as.character(na.omit(mapIds(org.Hs.eg.db, keys = background, column = "ENTREZID", keytype = "ENSEMBL")))
all_A3SS_gene_enid <- as.character(na.omit(mapIds(org.Hs.eg.db, keys = all_A3SS_gene, column = "ENTREZID", keytype = "ENSEMBL")))
all_A3SS_gene_enid <- all_A3SS_gene_enid[!is.na(all_A3SS_gene_enid)]
keytypes(org.Hs.eg.db)
background_enid <- bitr(background, fromType="ENSEMBL", toType="ENTREZID", OrgDb="org.Hs.eg.db")$ENTREZID
all_A3SS_gene_enid <- bitr(all_A3SS_gene, fromType="ENSEMBL", toType="ENTREZID", OrgDb="org.Hs.eg.db")$ENTREZID
A3SS_gene_0_enid <- bitr(A3SS_gene_0, fromType="ENSEMBL", toType="ENTREZID", OrgDb="org.Hs.eg.db")$ENTREZID
A3SS_gene_1_enid <- bitr(A3SS_gene_1, fromType="ENSEMBL", toType="ENTREZID", OrgDb="org.Hs.eg.db")$ENTREZID
A3SS_KEGG <- enrichKEGG(gene = all_A3SS_gene_enid,
organism = 'hsa',
universe = background_enid,
pvalueCutoff = 0.05)
head(A3SS_KEGG)
A3SS_0_KEGG <- enrichKEGG(gene = A3SS_gene_0_enid,
organism = 'hsa',
universe = background_enid,
pvalueCutoff = 0.05)
A3SS_1_KEGG <- enrichKEGG(gene = A3SS_gene_1_enid,
organism = 'hsa',
universe = background_enid,
pvalueCutoff = 0.05)
A3SS_mkk <- enrichMKEGG(gene = all_A3SS_gene_enid,
organism = 'hsa',
universe = background_enid)
A3SS_0_mkk <- enrichMKEGG(gene = A3SS_gene_0_enid,
organism = 'hsa',
universe = background_enid)
A3SS_1_mkk <- enrichMKEGG(gene = A3SS_gene_1_enid,
organism = 'hsa',
universe = background_enid)
head(A3SS_mkk)
A3SS_do <- DOSE::enrichDO(gene = all_A3SS_gene_enid,
ont = "DO",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
#universe = background_enid,
minGSSize = 5,
maxGSSize = 500,
qvalueCutoff = 0.05,
readable = FALSE)
A3SS_0_do <- DOSE::enrichDO(gene = A3SS_gene_0_enid,
ont = "DO",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
#universe = background_enid,
minGSSize = 5,
maxGSSize = 500,
qvalueCutoff = 0.05,
readable = FALSE)
A3SS_1_do <- DOSE::enrichDO(gene = A3SS_gene_1_enid,
ont = "DO",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
#universe = background_enid,
minGSSize = 5,
maxGSSize = 500,
qvalueCutoff = 0.05,
readable = FALSE)
head(A3SS_do)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/all_A3SS_gene_DO.pdf",height = 10,width = 15)
print(dotplot(A3SS_do,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(A3SS_do,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Pseudo_A3SS_gene_DO.pdf",height = 10,width = 15)
print(dotplot(A3SS_0_do,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(A3SS_0_do,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Real_A3SS_gene_DO.pdf",height = 10,width = 15)
print(dotplot(A3SS_1_do,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(A3SS_1_do,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
dgn <- enrichDGN(gene = all_A3SS_gene_enid,
#universe = background_enid,
qvalueCutoff = 0.05,
readable = TRUE)
dgn_0 <- enrichDGN(gene = A3SS_gene_0_enid,
#universe = background_enid,
qvalueCutoff = 0.05,
readable = TRUE)
dgn_1 <- enrichDGN(gene = A3SS_gene_1_enid,
#universe = background_enid,
qvalueCutoff = 0.05,
readable = TRUE)
head(dgn)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/all_A3SS_gene_DGN.pdf",height = 10,width = 15)
print(dotplot(dgn,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(dgn,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Pseudo_A3SS_gene_DGN.pdf",height = 10,width = 15)
print(dotplot(dgn_0,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(dgn_0,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Real_A3SS_gene_DGN.pdf",height = 10,width = 15)
print(dotplot(dgn_1,showCategory = 10,font.size = 16, title = "DO"))
enrichMap(dgn_1,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
library(ReactomePA)
A3SS_Path <- enrichPathway(gene = all_A3SS_gene_enid,
organism = "human",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
qvalueCutoff = 0.2,
universe = background_enid,
minGSSize = 10,
maxGSSize = 500,
readable = FALSE)
A3SS_0_Path <- enrichPathway(gene = A3SS_gene_0_enid,
organism = "human",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
qvalueCutoff = 0.2,
universe = background_enid,
minGSSize = 10,
maxGSSize = 500,
readable = FALSE)
A3SS_1_Path <- enrichPathway(gene = A3SS_gene_1_enid,
organism = "human",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
qvalueCutoff = 0.2,
universe = background_enid,
minGSSize = 10,
maxGSSize = 500,
readable = FALSE)
A3SS_BP_ego_1
A3SS_1_KEGG
dgn_1
print(dotplot(A3SS_BP_ego_1,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(A3SS_1_KEGG,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(dgn_1,showCategory = 10,font.size = 16,title = "BP"))
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/all_A3SS_gene_KEGG.pdf",height = 10,width = 15)
print(dotplot(A3SS_KEGG,showCategory = 10,font.size = 16, title = "BP"))
#suppressMessages(plotGOgraph(A3SS_KEGG,firstSigNodes = 15, useInfo = "all"))
enrichMap(A3SS_KEGG,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Pseudo_A3SS_gene_KEGG.pdf",height = 10,width = 15)
print(dotplot(A3SS_0_KEGG,showCategory = 10,font.size = 16, title = "BP"))
enrichMap(A3SS_0_KEGG,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Real_A3SS_gene_KEGG.pdf",height = 10,width = 15)
print(dotplot(A3SS_1_KEGG,showCategory = 10,font.size = 16, title = "BP"))
enrichMap(A3SS_1_KEGG,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Real_A3SS_gene_DGN.pdf",height = 10,width = 15)
print(dotplot(dgn_1,showCategory = 10,font.size = 16, title = "BP"))
#suppressMessages(plotGOgraph(A3SS_KEGG,firstSigNodes = 15, useInfo = "all"))
enrichMap(dgn_1,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/all_A3SS_gene_Pathway.pdf",height = 10,width = 15)
print(dotplot(A3SS_Path,showCategory = 10,font.size = 16, title = "BP"))
#suppressMessages(plotGOgraph(A3SS_Path,firstSigNodes = 15, useInfo = "all"))
enrichMap(A3SS_Path,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Pseudo_A3SS_gene_Pathway.pdf",height = 10,width = 15)
print(dotplot(A3SS_0_Path,showCategory = 10,font.size = 16, title = "BP"))
enrichMap(A3SS_0_Path,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/Real_A3SS_gene_Pathway.pdf",height = 10,width = 15)
print(dotplot(A3SS_1_Path,showCategory = 10,font.size = 16, title = "BP"))
enrichMap(A3SS_1_Path,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()
CompareGO_BP <- compareCluster(geneCluster = list(All = all_A3SS_gene, Pseudo = A3SS_gene_0, Real = A3SS_gene_1),
universe = background,
fun ="enrichGO",
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
CompareGO_MF <- compareCluster(geneCluster = list(All = all_A3SS_gene, Pseudo = A3SS_gene_0, Real = A3SS_gene_1),
universe = background,
fun ="enrichGO",
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "MF",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
CompareGO_CC <- compareCluster(geneCluster = list(All = all_A3SS_gene, Pseudo = A3SS_gene_0, Real = A3SS_gene_1),
universe = background,
fun ="enrichGO",
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "CC",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/A3SS_CompareGO.pdf", height = 8, width = 20)
print(dotplot(CompareGO_BP,showCategory = 10,font.size = 16,title = "A3SS GO BP"))
print(dotplot(CompareGO_MF,showCategory = 10,font.size = 16,title = "A3SS GO MF"))
print(dotplot(CompareGO_CC,showCategory = 10,font.size = 16,title = "A3SS GO CC"))
dev.off()
CompareKEGG <- compareCluster(geneCluster = list(All = all_A3SS_gene_enid, Pseudo = A3SS_gene_0_enid, Real = A3SS_gene_1_enid),
universe = background_enid,
fun = "enrichKEGG",
organism = "hsa",
pvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/A3SS_CompareKEGG.pdf", height = 8, width = 20)
print(dotplot(CompareKEGG,showCategory = 10,font.size = 16,title = "A3SS KEGG"))
dev.off()
CompareDO <- compareCluster(geneCluster = list(All = all_A3SS_gene_enid, Pseudo = A3SS_gene_0_enid, Real = A3SS_gene_1_enid),
fun = "enrichDO",
ont = "DO",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
universe = background_enid,
minGSSize = 5,
maxGSSize = 500,
qvalueCutoff = 0.05,
readable = FALSE)
library(ReactomePA)
ComparePathway <- compareCluster(geneCluster = list(All = all_A3SS_gene_enid, Pseudo = A3SS_gene_0_enid, Real = A3SS_gene_1_enid),
fun="enrichPathway",
organism = "human",
pvalueCutoff = 0.05,
pAdjustMethod = "BH",
qvalueCutoff = 0.2,
universe = background_enid,
minGSSize = 10,
maxGSSize = 500,
readable = FALSE)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A3SS/A3SS_ComparePathway.pdf", height = 8, width = 20)
print(dotplot(ComparePathway,showCategory = 10,font.size = 16,title = "A3SS Pathway"))
dev.off()
#### A5SS =======================================================================================================================================
load("/mnt/data5/BGI/UCB/tangchao/DSU2/A5SS/A5SS_psi_new.RData")
PSI <- A5SS_psi[, row.names(Cell_type)]
row.names(PSI) <- A5SS_psi$as2
rs <- rowSums(!is.na(PSI))
summary(rs)
PSI <- PSI[rs!=0, ]
rs <- rowSums(!is.na(PSI) & PSI != 0 & PSI != 1)
summary(rs)
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 0.000 0.000 0.000 3.632 1.000 960.000
sum(rs==0)
#[1] 2107
sum(rs==1)
#[1] 470
sum(rs>=1)
#[1] 923
all_A5SS_gene <- unique(A5SS_psi[A5SS_psi$as2 %in% row.names(PSI), "gene_id"])
length(all_A5SS_gene)
#[1] 2416
A5SS_gene_0 <- unique(A5SS_psi[A5SS_psi$as2 %in% names(rs)[rs==0], "gene_id"])
A5SS_gene_1 <- unique(A5SS_psi[A5SS_psi$as2 %in% names(rs)[rs>=1], "gene_id"])
length(A5SS_gene_0)
#[1] 1790
length(A5SS_gene_1)
#[1] 809
#### GO
A5SS_BP_ego <- enrichGO(gene = all_A5SS_gene,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
A5SS_MF_ego <- enrichGO(gene = all_A5SS_gene,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "MF",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
A5SS_CC_ego <- enrichGO(gene = all_A5SS_gene,
universe = background,
OrgDb = org.Hs.eg.db,
keyType = 'ENSEMBL',
ont = "CC",
pAdjustMethod = "BH",
pvalueCutoff = 0.05,
qvalueCutoff = 0.05)
pdf("/mnt/data5/BGI/UCB/tangchao/DSU2_GO/A5SS/all_A5SS_gene_GO.pdf",height = 10,width = 15)
print(dotplot(A5SS_BP_ego,showCategory = 10,font.size = 16,title = "BP"))
print(dotplot(A5SS_MF_ego,showCategory = 10,font.size = 16,title = "MF"))
print(dotplot(A5SS_CC_ego,showCategory = 10,font.size = 16,title = "CC"))
suppressMessages(plotGOgraph(A5SS_BP_ego,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(A5SS_MF_ego,firstSigNodes = 15, useInfo = "all"))
suppressMessages(plotGOgraph(A5SS_CC_ego,firstSigNodes = 15, useInfo = "all"))
enrichMap(A5SS_BP_ego,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(A5SS_MF_ego,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
enrichMap(A5SS_CC_ego,n = 30, vertex.label.font = 1,cex = 1, font.size = 1)
dev.off()