CARD官网：https://card.mcmaster.ca/
数据下载：https://card.mcmaster.ca/download
Github: https://github.com/arpcard/rgi

下载、安装

# 创建环境
conda create --name rgi
conda activate rgi
# 安装
conda install rgi \
--channel conda-forge --channel bioconda --channel defaults
# 指定版本安装
conda install rgi=5.1.1 \
--channel conda-forge --channel bioconda --channel defaults \

获取数据库

# https://card.mcmaster.ca/download/0/broadstreet-v3.2.2.tar.bz2
wget https://card.mcmaster.ca/latest/data
tar -xvf data ./card.json
# 设置数据库
rgi load --local -i /hwfsxx1/ST_HN/P18Z10200N0423/huty/databases/RGI/card.json
rgi database --version --local
# 3.2.7

mamba安装

mamba create --name rgi --channel conda-forge --channel bioconda --channel defaults rgi
mamba install --channel conda-forge --channel bioconda --channel defaults rgi=5.1.1
conda activate rgi
rgi load --card_json /hwfsxx1/ST_HN/P18Z10200N0423/huty/databases/RGI/card.json

使用
默认使用contig，过程prodigal预测ORF。也可提供蛋白序列直接注释。

rgi main \
-i input.fna -t protein \
-o output.card5.out \
--clean -n 32

main: Runs rgi application
-i: INPUT_SEQUENCE
-o: OUTPUT_FILE
-t {contig,protein} specify data input type (default = contig)
--clean: removes temporary files
-n: THREADS
-a {DIAMOND,BLAST} specify alignment tool (default = BLAST)

结果

https://github.com/arpcard/rgi#rgi-main-tab-delimited-output-details
geneset.card5.out.txt