构建自己物种的orgDb

1.首先安装eggnog-mapper软件

注释所需要的物种数据库网址如下，同时也可以用里面的脚本download_eggnog_data.py下载你所需要的数据库：

http://eggnogdb.embl.de/download/

python download_eggnog_data.py euk 下载euk数据库

eggnog-mapper有两种比对方式（直接调用emapper.py脚本即可）：

1. 基于hmmer的比对：建议序列少于1000条

$python /data1/spider/ytbiosoft/soft/eggnog-mapper-1.0.3/emapper.py -m hmmer -i test.fasta -d euk -o test_euk（输出文件前缀）

2. 基于diamond的比对：序列大于1000条(不需要指定数据库)

$python /data1/spider/ytbiosoft/soft/eggnog-mapper-1.0.3/emapper.py -m diamond -i 你的物种所有蛋白序列 -o sesame（输出文件前缀）

2. 对生成的文件修改

结果会生成一个sesame.emapper.annotations的文件。查看文件会发现有许多以#开头的行，要删掉这些没用的行。注意别删掉表头。

sesame.emapper.annotations

所以需要删掉#开头的行以及表头的#，但不要删表头

$sed -i 's/#//' sesame.emapper.annotations  -i就在源文件修改 s替换 /空字符

此时的sesame.emapper.annotations就可以拿来构建orgDb了。

3. 根据eggnog-mapper注释结果构建orgDb

1. 安装R包

library(tidyverse)
library(stringr)
library(KEGGREST)
library(AnnotationForge)

除了KEGGREST以外的三个都可以用install.packages()安装

>if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")


>BiocManager::install("KEGGREST")

安装好之后就可以构建自己的orgDb了

2. 构建orgDb

library(tidyverse)
library(stringr)
library(KEGGREST)
library(AnnotationForge)


#' Title
#'
#' @param f_emapper_anno eggnog-mapper annotation result
#' @param author Who is the creator of this package? like "xxx "
#' @param tax_id The Taxonomy ID that represents your organism. (NCBI has a nice online browser for finding the one you need)
#' @param genus Single string indicating the genus
#' @param species Single string indicating the species
#'
#' @return OrgDb name
#' @export
#'
#' @examples
makeOrgPackageFromEmapper <- function(f_emapper_anno,
                                      author,
                                      tax_id = "0",
                                      genus = "default",
                                      species = "default") {
  
  # read emapper result
  emapper <- read_delim(f_emapper_anno,
                        "\t", escape_double = FALSE, trim_ws = TRUE)
  
  # extract gene name from emapper
  gene_info <- emapper %>%
    dplyr::select(GID = query_name, GENENAME = `eggNOG annot`) %>%
    na.omit()
  
  # extract go annotation from emapper
  gos <- emapper %>%
    dplyr::select(query_name, GO_terms) %>%
    na.omit()
  
  gene2go = data.frame(GID = character(),
                       GO = character(),
                       EVIDENCE = character())
  
  for (row in 1:nrow(gos)) {
    the_gid <- gos[row, "query_name"][[1]]
    the_gos <- str_split(gos[row,"GO_terms"], ",", simplify = FALSE)[[1]]
    
    df_temp <- data_frame(GID = rep(the_gid, length(the_gos)),
                          GO = the_gos,
                          EVIDENCE = rep("IEA", length(the_gos)))
    gene2go <- rbind(gene2go, df_temp)
  }
  
  # extract kegg pathway annotation from emapper
  gene2ko <- emapper %>%
    dplyr::select(GID = query_name, Ko = KEGG_KOs) %>%
    na.omit()
  
  load(file = "kegg_info.RData")
  gene2pathway <- gene2ko %>% left_join(ko2pathway, by = "Ko") %>%
    dplyr::select(GID, Pathway) %>%
    na.omit()


  # make OrgDb
  makeOrgPackage(gene_info=gene_info,
                 go=gene2go,
                 ko=gene2ko,
                 pathway=gene2pathway,
                 # gene2pathway=gene2pathway,
                 version="0.0.2",
                 maintainer=author,
                 author=author,
                 outputDir = ".",
                 tax_id=tax_id,
                 genus=genus,
                 species=species,
                 goTable="go")
  
  my_orgdb <- str_c("org.", str_to_upper(str_sub(genus, 1, 1)) , species, ".eg.db", sep = "")
  return(my_orgdb)
}


my_orgdb <- makeOrgPackageFromEmapper("input/sesame.emapper.annotations",
                                      "zhangxudong ",
                                      tax_id = "4182",
                                      genus = "Sesamum",
                                      species = "indicum")

跑完代码就会生成一个org.Sindicum.eg.db的文件夹。此时就可以在Rstiduo里面安装这个包了。