All R analyses were performed under R version 4.1.2 and the corresponding Bioconductor version 3.14. Specific package versions are managed via renv
and details can be found in the corresponding renv.lock
file.
All python analyses are performed under Python version 3.8.9. Specific package versions are managed via Miniconda
. The specifications for the primary virtual environment is in the microbe_trait_env.yml
file. Since we also use QIIME2
and picrust2
, separate conda environments were utilized for each software respectively due to dependency conflicts. Specifications for the QIIME2
2022.2 environment can be found in the qiime2-2022.2-py38-linux-conda.yml
file (for different OS, please refer to the main QIIME2
documentation for instructions to install version 2022.2 in your machine).
All analyses are in Jupyter Notebooks located in the analysis
folder.
- Placeholder
Most analyses are located within reproducible jupyter notebooks. However, there are some computations that require more resources and therefore are ran as stand-alone scripts or as part of more reproducible workflows.
Intensive computing steps in R were performed using the targets
package. The entire pipeline was broken down into smaller "steps" for ease of processing. The file run.R
contains code to choose between different pipelines to run.
Individual mini-pipelines include: - Placeholder
metaphlan_db.R
defines functions to process the MetaPhlAn3 marker information files. db_preprocess.R
defines functions to pre-process the database into BiocSet
format. hmp_preprocess.R
defines functions to pre-process the HMP data data files (newest release). In order to conveniently access the MetaCyc pathway class hierarchy, the package pythoncyc
is used. Since this package is not distributed via pip
or conda
, please create a new conda or virtual environment, and then use the manual installation instructions when your desired conda environment is activated. Due to the perks of the pythoncyc
library, users need to also install the associated PathwayTools
program (v. 25.1) and run it with the python API open (see instructions in the link above). This step doesn't need to be repeated (hence not included in the major pipelines) and the product of this step is saved as a binary file called metacyc_parse.rds
in the databases
folder.
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