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implementation.md

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Implementation

1. Calculate the interaction between species.

Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b2.hn.b123.bacteria.abundance.csv  data/interaction/b2.hn.b123
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b2.hn.b101112.bacteria.abundance.csv data/interaction/b2.hn.b101112
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b2.hn.b131415.bacteria.abundance.csv data/interaction/b2.hn.b131415
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b2.hn.b161718.bacteria.abundance.csv data/interaction/b2.hn.b161718
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b2.hn.b192021.bacteria.abundance.csv data/interaction/b2.hn.b192021
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b2.hn.b222324.bacteria.abundance.csv data/interaction/b2.hn.b222324
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b2.hn.b456.bacteria.abundance.csv data/interaction/b2.hn.b456
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b2.hn.b789.bacteria.abundance.csv data/interaction/b2.hn.b789
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b1.ln.b101112.bacteria.abundance.csv data/interaction/b1.ln.b101112
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b1.ln.b123.bacteria.abundance.csv data/interaction/b1.ln.b123
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b1.ln.b131415.bacteria.abundance.csv data/interaction/b1.ln.b1314115
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b1.ln.b161718.bacteria.abundance.csv data/interaction/b1.ln.b161718
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b1.ln.b192021.bacteria.abundance.csv data/interaction/b1.ln.b192021
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b1.ln.b222324.bacteria.abundance.csv data/interaction/b1.ln.b222324
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b1.ln.b456.bacteria.abundance.csv data/interaction/b1.ln.b456
Rscript script/a1.calculate_alpamatrix.with.plot.r data/abandence/b1.ln.b789.bacteria.abundance.csv data/interaction/b1.ln.b789

2. merge interaction table.

cd data/interaction/
cat b1*interaction.csv > b3.ln.interaction.csv
grep -v '""' b3.ln.interaction.csv > b3.ln.csv
cut -f 2,3,4 -d ',' b3.ln.csv > b3.ln.interaction.csv
rm b3.ln.csv
cat b2*interaction.csv > b4.hn.interaction.csv
grep -v '""' b4.hn.interaction.csv > b4.hn.csv
cut -f 2,3,4 -d ',' b4.hn.csv > b4.hn.interaction.csv
rm b4.hn.csv
cd ../..

3. Annotation pathway and gene in bacteria.

abun='data/otu/16s.abun.tsv'
fasta='data/otu/16s_sequence.fa'
output='data/otu/mic'
python script/otu2abun.py -i data/otu/16s_sequence.fa -o data/otu/16s.abun.tsv 
echo "MicFunPred_run_pipeline.py -i ${abun} -r ${fasta} -o ${output} -t 10 --verbose"
MicFunPred_run_pipeline.py -i ${abun} -r ${fasta} -o ${output} -t 10 --verbose

cp ${output}/

4. extract useful message from annotation files.

cp data/annotation/mic/out.blast data/annotation/species.txt
cp data/annotation/mic/CAZymes_metagenome/CAZymes_metagenome.tsv.gz data/annotation
cp data/annotation/mic/COG_metagenome/COG_metagenome.tsv.gz data/annotation
cp data/annotation/mic/KO_metagenome/KEGG_pathways_MinPath_prunned.tsv.gz data/annotation
cp data/annotation/mic/KO_metagenome/KO_metagenome_MinPath_prunned.tsv.gz  data/annotation
cp data/annotation/mic/MetaCyc_metagenome/Pathway_summarize_by_Types.tsv.gz  data/annotation/cyc.tsv.gz
cp data/annotation/mic/Pfam_metagenome/Pfam_metagenome.tsv.gz  data/annotation
cp data/annotation/mic/TIGRFAM_metagenome/TIGRFAM_metagenome.tsv.gz  data/annotation

gunzip  data/annotation/CAZymes_metagenome.tsv.gz
gunzip data/annotation/COG_metagenome.tsv.gz
gunzip data/annotation/KEGG_pathways_MinPath_prunned.tsv.gz
gunzip data/annotation/KO_metagenome_MinPath_prunned.tsv.gz
gunzip data/annotation/cyc.tsv.gz
gunzip data/annotation/Pfam_metagenome.tsv.gz
gunzip data/annotation/TIGRFAM_metagenome.tsv.gz

5. get species name.

cut -f 1,2  data/annotation/species.txt > data/annotation/species_name.txt

6. combine pathway with interaction.

Rscript script/a2.combine.gene.interaction.r data/annotation/CAZymes_metagenome.tsv data/interaction/b3.ln.interaction.csv data/ml/ln.ml.cazymes 
Rscript script/a2.combine.gene.interaction.r data/annotation/COG_metagenome.tsv data/interaction/b3.ln.interaction.csv data/ml/ln.ml.cog 
Rscript script/a2.combine.gene.interaction.r data/annotation/KEGG_pathways_MinPath_prunned.tsv data/interaction/b3.ln.interaction.csv data/ml/ln.ml.kegg
Rscript script/a2.combine.gene.interaction.r data/annotation/KO_metagenome_MinPath_prunned.tsv data/interaction/b3.ln.interaction.csv data/ml/ln.ml.ko 
Rscript script/a2.combine.gene.interaction.r data/annotation/Pfam_metagenome.tsv data/interaction/b3.ln.interaction.csv data/ml/ln.ml.pfam 
Rscript script/a2.combine.gene.interaction.r data/annotation/TIGRFAM_metagenome.tsv data/interaction/b3.ln.interaction.csv data/ml/ln.ml.tigrfam 
#
Rscript script/a2.combine.gene.interaction.r data/annotation/CAZymes_metagenome.tsv data/interaction/b4.hn.interaction.csv data/ml/hn.ml.cazymes 
Rscript script/a2.combine.gene.interaction.r data/annotation/COG_metagenome.tsv data/interaction/b4.hn.interaction.csv data/ml/hn.ml.cog 
Rscript script/a2.combine.gene.interaction.r data/annotation/KEGG_pathways_MinPath_prunned.tsv data/interaction/b4.hn.interaction.csv data/ml/hn.ml.kegg
Rscript script/a2.combine.gene.interaction.r data/annotation/KO_metagenome_MinPath_prunned.tsv data/interaction/b4.hn.interaction.csv data/ml/hn.ml.ko 
Rscript script/a2.combine.gene.interaction.r data/annotation/Pfam_metagenome.tsv data/interaction/b4.hn.interaction.csv data/ml/hn.ml.pfam 
Rscript script/a2.combine.gene.interaction.r data/annotation/TIGRFAM_metagenome.tsv data/interaction/b4.hn.interaction.csv data/ml/hn.ml.tigrfam

7. prepare machine learning environment.

mamba create -n py38 python=3.8.17
mamba activate py38
mamba install -c creditx hpsklearn
pip install git+https://github.com/hyperopt/hyperopt-sklearn
mamba install -c conda-forge boruta_py
pip install boostaroota
pip install pickle
pip install shap
pip install matplotlib
pip install seaborn
pip install tensorflow
pip install pydot
pip install graphviz
pip install numpy==1.23
#pip install numpy==1.23.5
pip install plotly

8. run with cluster.

#!/bin/bash
#SBATCH -o /public/home/2022122/xugang/condaenv/BCP/script/cazy_1.%j.out
#SBATCH -e /public/home/2022122/xugang/condaenv/BCP/script/cazy_1.%j.error
#SBATCH --partition=Gnode
#SBATCH -J carzy
#SBATCH -N 1
#SBATCH -n 28

source /public/home/2022122/xugang/bashrc

conda run -n py38 python learn_code_meaning.py