metaprof v2.2

A quick profiling about metagenomes data --update metaphlan4

environment

• biopython>=1.76
• bowtie2>=2.3.5.1
• fastp>=0.20.1
• metaphlan>=4.1.0
• numpy>=1.18.4
• pandas>=1.0.3
• pigz>=2.3.4
• samtools>=1.9
• seqkit>=0.12.1
• snakemake>=5.14.0
• kraken2>=2.1.1
• bracken>=2.5

install

git clone https://github.com/weiting-liang/metaprof.git

cd metaprof
conda env create -n metaprof -f ./rules/env.yaml
conda activate metaprof

#database prepare
human reference https://github.com/marbl/CHM13

mkdir /path/database
cd database && mkdir humanhost && cd humanhost 
wget https://s3-us-west-2.amazonaws.com/human-pangenomics/T2T/CHM13/assemblies/analysis_set/chm13v2.0.fa.gz
gzip chm13v2.0.fa.gz -d
mkdir bowtie2_index && cd bowtie2_index
bowtie2-build ../chm13v2.0.fa chm13v2

metaphlan3

cd /path/database
mkdir metaphlan && cd metaphlan
metaphlan --install --index mpa_vOct22_CHOCOPhlAnSGB_202212 --bowtie2db metaphlan_database

kraken2

cd /path/database
mkdir kraken2 && cd kraken_pub
wget https://genome-idx.s3.amazonaws.com/kraken/k2_standard_20210517.tar.gz
tar -xzvf k2_standard_20210517.tar.gz -C ./k2_standard_20210517

run

• change the samples.txt to adapt to your data: separator should be "\t": id^Ifq1^Ifq2$
• custom the config.yaml database's path and parameters

#dry run
snakemake --snakefile rules/profile.smk -n
#test
snakemake --snakefile rules/profile.smk --core 16 2> smk.log &
#cluster: custom the cluster.yaml
nohup sh snakemake.sh &

output

2.results/
filter_summary.txt
metaphlan4.profile.merge.txt bracken.merged.abundance.profile.*.tsv

#assay:
1.assay
01.trimming/
02.rmhost/
03.profile/
benchmarks/ #check the cpu's time and max_vms to optimize the cluster's parameters
cluster_logs/
logs/ #find programs' errors

references

https://github.com/ohmeta/metapi/blob/master/metapi/Snakefile

https://github.com/liu930724/meta_profile