## ----style, echo=FALSE, results="asis", message=FALSE--------------------
BiocStyle::markdown()
knitr::opts_chunk$set(tidy = FALSE,
                      warning = FALSE,
                      message = FALSE)

## ----echo=FALSE, results='hide', message=FALSE---------------------------
library(DOSE)
library(GO.db)
library(org.Hs.eg.db)
library(clusterProfiler)

## ------------------------------------------------------------------------
x <- c("GPX3",  "GLRX",   "LBP",   "CRYAB", "DEFB1", "HCLS1",   "SOD2",   "HSPA2", 
       "ORM1",  "IGFBP1", "PTHLH", "GPC3",  "IGFBP3","TOB1",    "MITF",   "NDRG1", 
       "NR1H4", "FGFR3",  "PVR",   "IL6",   "PTPRM", "ERBB2",   "NID2",   "LAMB1", 
       "COMP",  "PLS3",   "MCAM",  "SPP1",  "LAMC1", "COL4A2",  "COL4A1", "MYOC",  
       "ANXA4", "TFPI2",  "CST6",  "SLPI",  "TIMP2", "CPM",     "GGT1",   "NNMT",
       "MAL",   "EEF1A2", "HGD",   "TCN2",  "CDA",   "PCCA",    "CRYM",   "PDXK",  
       "STC1",  "WARS",  "HMOX1", "FXYD2", "RBP4",   "SLC6A12", "KDELR3", "ITM2B")
eg = bitr(x, fromType="SYMBOL", toType="ENTREZID", annoDb="org.Hs.eg.db")
head(eg)

## ------------------------------------------------------------------------
idType("org.Hs.eg.db")

## ------------------------------------------------------------------------
ids <- bitr(x, fromType="SYMBOL", toType=c("UNIPROT", "ENSEMBL"), annoDb="org.Hs.eg.db")
head(ids)

## ------------------------------------------------------------------------
library("DOSE")
data(geneList)
gene <- names(geneList)[abs(geneList) > 2]
head(gene)
ggo <- groupGO(gene     = gene,
               organism = "human",
               ont      = "BP",
               level    = 3,
               readable = TRUE)
head(summary(ggo))

## ------------------------------------------------------------------------
ego <- enrichGO(gene          = gene,
                universe      = names(geneList),
                organism      = "human",
                ont           = "CC",
                pAdjustMethod = "BH",
                pvalueCutoff  = 0.01,
                qvalueCutoff  = 0.05,
                readable      = TRUE)
head(summary(ego))

## ----eval=FALSE----------------------------------------------------------
## ego2 <- gseGO(geneList     = geneList,
##               organism     = "human",
##               ont          = "CC",
##               nPerm        = 1000,
##               minGSSize    = 120,
##               pvalueCutoff = 0.01,
##               verbose      = FALSE)

## ------------------------------------------------------------------------
kk <- enrichKEGG(gene         = gene,
                 organism     = "human",
                 pvalueCutoff = 0.05, 
                 readable     = TRUE,
                 use_internal_data = TRUE)
head(summary(kk))

## ------------------------------------------------------------------------
kk2 <- gseKEGG(geneList     = geneList,
               organism     = "human",
               nPerm        = 1000,
               minGSSize    = 120,
               pvalueCutoff = 0.05,
               verbose      = FALSE,
               use_internal_data = TRUE)
head(summary(kk2))

## ----eval=FALSE----------------------------------------------------------
## david <- enrichDAVID(gene = gene,
##                      idType = "ENTREZ_GENE_ID",
##                      listType = "Gene",
##                      annotation = "KEGG_PATHWAY",
##                      david.user = "clusterProfiler@hku.hk")

## ----fig.height=5, fig.width=6-------------------------------------------
barplot(ggo, drop=TRUE, showCategory=12)

## ----fig.height=5, fig.width=8-------------------------------------------
barplot(ego, showCategory=8)

## ------------------------------------------------------------------------
dotplot(ego)

## ----fig.cap="enrichment map of enrichment result", fig.align="center", fig.height=16, fig.width=16----
enrichMap(ego)

## ----fig.height=14, fig.width=14-----------------------------------------
cnetplot(ego, categorySize="pvalue", foldChange=geneList)

## ----fig.height=14, fig.width=14-----------------------------------------
cnetplot(kk, categorySize="geneNum", foldChange=geneList)

## ----fig.cap="plotting gsea result", fig.align="center", fig.height=6, fig.width=8----
gseaplot(kk2, geneSetID = "hsa04145")

## ----fig.height=12, fig.width=8------------------------------------------
plotGOgraph(ego)

## ----eval=FALSE----------------------------------------------------------
## library("pathview")
## hsa04110 <- pathview(gene.data  = geneList,
##                      pathway.id = "hsa04110",
##                      species    = "hsa",
##                      limit      = list(gene=max(abs(geneList)), cpd=1))

## ------------------------------------------------------------------------
data(gcSample)
lapply(gcSample, head)

## ------------------------------------------------------------------------
ck <- compareCluster(geneCluster = gcSample, fun = "enrichKEGG", use_internal_data = TRUE)
head(summary(ck))

## ------------------------------------------------------------------------
## formula interface
mydf <- data.frame(Entrez=c('1', '100', '1000', '100101467',
                       '100127206', '100128071'),
                   group = c('A', 'A', 'A', 'B', 'B', 'B'),
                   othergroup = c('good', 'good', 'bad', 'bad',
                       'good', 'bad'))
xx.formula <- compareCluster(Entrez~group, data=mydf, fun='groupGO')
head(summary(xx.formula))

## formula interface with more than one grouping variable
xx.formula.twogroups <- compareCluster(Entrez~group+othergroup,
                                       data=mydf, fun='groupGO')
head(summary(xx.formula.twogroups))

## ----fig.height=8, fig.width=8-------------------------------------------
plot(ck)

## ----echo=FALSE----------------------------------------------------------
sessionInfo()