做植物是一件比较艰苦的事情，不但资源少，而且有限的资源未必还能用的好，就拿Bioconductor上的注释包来说吧，我在「Bioconductor」不要轻易相信AnnotationHub的物种注释包, 里面就提到拟南芥的物种包用的注释其实一直都没有更新。究其原因，是因为拟南芥的物种包里的注释一直是从TAIR的FTP下载，而我另一篇文章TAIR周期性更新的注释原来不在FTP服务器上也说了，最新的拟南芥注释信息是要在另外的地方进行下载。所以，我写了「Bioconductor」再次提醒，研究植物的不要轻易相信你用的注释包， 让大家尝试用enricher解决问题。

但是生活不能苟且，我好歹在生信圈搬了几年砖，遇到困难不能退缩，于是我决定自己构建一个拟南芥的物种包。代码如下：

library(RSQLite)
library(AnnotationForge)
options(stringsAsFactors = F)

# GENE-GO注释的数据框
go_df <- read.table("F:/Project/org.At.tair.db/ATH_GO_TERM.txt",
                      sep="\t", header = FALSE,
                      as.is = TRUE)
go_df$V3 <- ifelse(go_df$V3 == "C", "CC",
                     ifelse(go_df$V3 == "P", "BP",
                            ifelse(go_df$V3 == "F", "MF", "")))
colnames(go_df) <- c("GID","GO","ONTOLOGY","EVIDENCE")


# GENE-PUB的数据框
pub_df <- read.table("F:/Project/org.At.tair.db/Locus_Published_20171231.txt",
                     sep="\t",
                     header = TRUE)

## 只选择AT开头的基因
pub_df <- pub_df[grepl(pattern = "^AT\\d", pub_df$name),]
pub_df <- cbind(GID=do.call(rbind,strsplit(pub_df$name, split = "\\."))[,1],
                pub_df)
## pubmed_id 不能为空
pub_df <- pub_df[!is.na(pub_df$PMID),]

colnames(pub_df) <- c("GID","GENEID","REFID",
                      "PMID","PUBYEAR")

# GENE-SYMBOL的注释数据库
symbol_df <- read.table("F:/Project/org.At.tair.db/gene_aliases_20171231.txt",
                        sep = "\t",
                        header = TRUE)
symbol_df <- symbol_df[grepl(pattern = "^AT\\d", symbol_df$name),]
colnames(symbol_df) <- c("GID","SYMBOL","FULL_NAME")


# GENE-FUNCTION
func_df <- read.table("F:/Project/org.At.tair.db/Araport11_functional_descriptions_20171231.txt",
                      sep = "\t",
                      header=TRUE)
func_df <- func_df[grepl(pattern = "^AT\\d", func_df$name),]
func_df <- cbind(GID=do.call(rbind,strsplit(func_df$name, split = "\\."))[,1],
                  func_df)
colnames(func_df) <- c("GID","TXID","GENE_MODEL_TYPE",
                       "SHORT_DESCRIPTION",
                       "CURATOR_SUMMARY",
                       "COMPUTATIONAL_DESCRIPTION")
## 去重复行
go_df <- go_df[!duplicated(go_df),]
go_df <- go_df[,c(1,2,4)]
pub_df <- pub_df[!duplicated(pub_df),]
symbol_df <- symbol_df[!duplicated(symbol_df),]
func_df <- func_df[!duplicated(func_df),]

makeOrgPackage(go=go_df,
               pub_info = pub_df,
               symbol_info = symbol_df,
               function_info = func_df,
               version = "0.1",
               maintainer = "xuzhougeng <xuzhougeng@163.com>",
               author="xuzhogueng <xuzhougeng@163.com>",
               outputDir = "F:/Project/org.At.tair.db",
               tax_id = "3702",
               genus = "At",
               species = "tair10",
               goTable = "go"
  
)

最后会在指定目录下生成"org.Atair10.eg.db", 然后就可以用

install.packages("./org.Atair10.eg.db", repos = NULL,
                 type = "source")

而且我测试了，能和Y叔的clusterProfiler完美结合

library(org.Atair10.eg.db)
org <- org.Atair10.eg.db
ego_down <-enrichGO(gene = DEG_GENES, 
         OrgDb = org,
         keyType = "GID",
         ont = "BP"
         ) 

目前我是自己用为主，如果你们有需要，可以按照如下代码进行安装

# 解决依赖包的问题
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("org.At.tair.db", version = "3.8")
# 安装我的注释包
install.packages("https://raw.githubusercontent.com/xuzhougeng/org.At.tair.db/master/org.Atair10.eg.db.tgz", repos=NULL, type="source")

出现问题，欢迎在我的GitHubhttps://github.com/xuzhougeng/org.At.tair.db上提出issue

参考资料

• http://bioconductor.org/packages/release/bioc/vignettes/AnnotationForge/inst/doc/MakingNewOrganismPackages.html