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）：
- 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）
- 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
- 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
- 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 <xxx@xxx.xx>"
#' @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 <zhangxudong@genek.tv>",
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。
