Welcome to GOcats’ documentation!¶
GOcats is an Open Biomedical Ontology (OBO) parser and categorizing utility–currently specialized for the Gene Ontology (GO)–which can help scientists interpret large-scale experimental results by organizing redundant and highly- specific annotations into customizable, biologically-relevant concept categories. Concept subgraphs are defined by lists of keywords created by the user.
Full API documentation, userguide, and tutorial can be found on readthedocs
- Currently, the GOcats package can be used to:
- Create subgraphs of GO which each represent a user-specified concept.
- Map specific, or fine-grained, GO terms in a Gene Annotation File (GAF) to an arbitrary number of concept categories.
- Explore the Gene Ontology graph within a Python interpreter.
Please cite the GitHub repository until our manuscript is accepted for publication: https://github.com/MoseleyBioinformaticsLab/GOcats.git
GOcats runs under Python 3.4+ and is available through python3-pip. Install via pip or clone the git repo and install the following dependencies and you are ready to go!
Install on Linux¶
Dependencies should be automatically installed using this method. It is strongly recommended that you install with this method. .. code:: bash
pip3 install gocats
GitHub Package installation¶
Make sure you have git installed:
cd ~/ git clone https://github.com/MoseleyBioinformaticsLab/GOcats.git
Install on Windows¶
Windows version not yet available; sorry about that.
Subgraphs can be created from the command line.
python3 -m gocats create_subgraphs /path_to_ontology_file ~/GOcats/gocats/exampledata/examplecategories.csv ~/Output --supergraph_namespace=cellular_component --subgraph_namespace=cellular_component --output_termlist
Mapping files can be found in the output directory:
- GC_content_mapping.json_pickle # A python dictionary with category-defining GO terms as keys and a list of all subgraph contents as values.
- GC_id_mapping.json_pickle # A python dictionary with every GO term of the specified namespace as keys and a list of category root terms as values.
GAF mappings can also be made from the command line:
python3 -m gocats categorize_dataset YOUR_GAF.goa YOUR_OUTPUT_DIRECTORY/GC_id_mapping.json_pickle YOUR_OUTPUT_DIRECTORY MAPPED_DATASET_NAME.goa
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Copyright (c) 2017, Eugene W. Hinderer III, Hunter N.B. Moseley All rights reserved.
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