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Code for reproducing results published in scientific journals, regarding tilapia and perch gut microbiota.

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yanxianl/Kizito_tilapia-perch-microbiota_2021

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Title here

doi here

Abstract here

File organization

root
├── code
│   ├── 00_setup.ipynb
│   ├── 01_qiime2_part1.html
│   ├── 01_qiime2_part1.ipynb
│   ├── 02_feature_filtering.html
│   ├── 02_feature_filtering.Rmd
│   ├── 03_qiime2_part2.html
│   ├── 03_qiime2_part2.ipynb
│   ├── 04_qiime2R.html
│   ├── 04_qiime2R.Rmd
│   ├── 05_taxonomy_tilapia.html
│   ├── 05_taxonomy_tilapia.Rmd
│   ├── 06_alpha_diversity_tilapia.html
│   ├── 06_alpha_diversity_tilapia.Rmd
│   ├── 07_beta_diversity_tilapia.html
│   ├── 07_beta_diversity_tilapia.Rmd
│   ├── 08_differential_analysis_tilapia.html
│   ├── 08_differential_analysis_tilapia.Rmd
│   ├── 09_taxonomy_perch.html
│   ├── 09_taxonomy_perch.Rmd
│   ├── 10_alpha_diversity_perch.html
│   ├── 10_alpha_diversity_perch.Rmd
│   ├── 11_beta_diversity_perch.html
│   ├── 11_beta_diversity_perch.Rmd
│   ├── 12_differential_analysis_perch.html
│   ├── 12_differential_analysis_perch.Rmd
│   ├── functions
│   │   ├── plot_betadisper.R
│   │   ├── plot_frequency.R
│   │   ├── plot_heatmap.R
│   │   └── plot_prevalence.R
│   └── README.md
├── data
│   ├── raw
│   │   ├── fastq
│   │   ├── qPCR
│   │   └── README.md
│   ├── reference
│   │   ├── silva_132_99_16S.fna
│   │   ├── silva_132_consensus_taxonomy_l7.txt 
│   │   ├── sepp-refs-silva-128.qza 
│   │   └── README.md
│   ├── intermediate
│   │   ├── filtering
│   │   ├── qiime2 
│   │   ├── qiime2R 
│   │   ├── permanova
│   │   └── maaslin2
│   └── metadata.tsv
├── result
│    ├── figure
│    │   ├── perch
│    │   └── tilapia
│    └── table
│        ├── perch
│        └── tilapia
├── Kizito_tilapia-perch-microbiota_2021.Rproj
├── LICENSE.md
└── README.md

How to regenerate this repository

Dependencies and locations

  • Miniconda3 should be located in your HOME directory.
  • QIIME2 (2021.4) should be installed within a Miniconda3 environment and named as qiime2-2021.4.
    • QIIME2 library: DEICODE (0.2.3) should be installed within the qiime2 conda environment.
    • grabseqs (0.7.0) should be installed within the qiime2 conda environment.
  • Pandoc (2.5) should be located in your PATH.
  • R (4.0.5) should be located in your PATH.
  • R packages and versions: see session information at the end of each rmarkdown report.

Running the analysis

All the code should be run from the project's root directory.

1.Clone or download this github repository to your local computer.

# clone the github repository
git clone https://github.com/yanxianl/Kizito_tilapia-perch-microbiota_2021.git

# delete the following folders
rm -rf \
  data/intermediate/qiime2/compare_runs/ \
  data/intermediate/qiime2/core_metrics_results*/ \
  data/intermediate/qiime2/rpca*/ 

2.Download raw sequence data, SILVA132 reference database and SILVA128 SEPP reference phylogeny (code/00_setup.ipynb).

# activate qiime2 environment
source $HOME/miniconda3/bin/activate
conda activate qiime2-2021.4

# launch jupyter notebook and run code/00_setup.ipynb interactively
jupyter notebook

# exit jupyter notebook after running the code by pressing Ctrl   c in the terminal

3.Sequence denoising (DADA2) and taxonomic assignment.

jupyter nbconvert --execute --to html code/01_qiime2_part1.ipynb

4.Filter the feature tables to remove: 1).chloroplast/mitochondria sequences and those without a phylum-level taxonomic assignment; 2).low-prevalence features that only present in one sample; 3).contaminating features.

Rscript -e "rmarkdown::render('code/02_feature_filtering.Rmd')"

5.Phylogeny and core-metrics-results.

jupyter nbconvert --execute --to html code/03_qiime2_part2.ipynb

6.Import qiime2 artifacts into R.

Rscript -e "rmarkdown::render('code/04_qiime2R.Rmd')"

7.Downstream data analysis to generate main results presented in the tilapia paper.

# taxonomic analysis
Rscript -e "rmarkdown::render('code/05_taxonomy_tilapia.Rmd')" &&
Rscript -e "rmarkdown::render('code/06_alpha_diversity_tilapia.Rmd')" &&
Rscript -e "rmarkdown::render('code/07_beta_diversity_tilapia.Rmd')" &&
Rscript -e "rmarkdown::render('code/08_differential_analysis_tilapia.Rmd')"

8.Downstream data analysis to generate main results presented in the perch paper.

# taxonomic analysis
Rscript -e "rmarkdown::render('code/09_taxonomy_perch.Rmd')" &&
Rscript -e "rmarkdown::render('code/10_alpha_diversity_perch.Rmd')" &&
Rscript -e "rmarkdown::render('code/11_beta_diversity_perch.Rmd')" &&
Rscript -e "rmarkdown::render('code/12_differential_analysis_perch.Rmd')"

To-do

  • Add a driver script to automate all the analysis, e.g., make.

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