The initial work is available at https://doi.org/10.3389/fpls.2019.01329, and many improvements have been made since then. The workflow is illustrated in Figure 1.
This repository contains everything needed to perform Taxonomically Informed Metabolite Annotation.
It is provided with an example from well-known pharmacopoeia plants.
Here is what you minimally need:
- A feature list with or without candidate annotations, if you are using GNPS, it can be your GNPS job ID.
- The source organism of the extract you are annotating, if you are associating metadata within GNPS, it can be your GNPS job ID.
- An edge list, if you are using GNPS, it can be your GNPS job ID.
Optionally, you may want to add:
- An in-house structure-organism pairs library (we provide LOTUS as starting point for each user)
- Your own manual or automated annotations (we currently support annotations coming from ISDB and SIRIUS)
git clone git@github.com:taxonomicallyinformedannotation/tima-python.git
cd tima-pythonIf you are using Windows, you will need to install Choco.
Then run:
choco install curl
choco install gzip
choco install unzip
choco install wgetPlease also follow the procedure described here to ensure files will be proberly encoded.
docker build -t tima-python . # optional
docker run -it --rm -v $PWD:/app tima-pythonconda env create -f environment.yml &&
conda activate tima-python# copy the default params to adapat to your data later on
cp -R config/default config/paramsbash src/get_lotus.sh &&
python src/prepare_lotus.py &&
# python prepare_closed.py && # only if you have access to it
python src/prepare_library.py &&
python src/prepare_adducts.py &&# normally it would be 'python src/process_spectra.py' but for now we have to think about it.
# instead we provide an example file coming from the new ISDB.
# It also works with annotations coming from GNPS (see next steps)
bash src/get_example_isdb.sh# depending on the annotation tool you used
python src/prepare_gnps.py && # optional
python src/prepare_isdb.pypython src/prepare_edges.py &&
python src/prepare_features_components.py &&
python src/prepare_features_classification.py bash src/get_gnverifier.sh &&
python src/prepare_taxa.py# python process_annotations.pyNOTE: you can use --help or -h argument for all .py steps to get more info