https://github.com/barricklab/widespread-recurrent-part-variants
Analysis code for identifying genetic part variants in engineered plasmids
https://github.com/barricklab/widespread-recurrent-part-variants
Last synced: 4 months ago
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Analysis code for identifying genetic part variants in engineered plasmids
- Host: GitHub
- URL: https://github.com/barricklab/widespread-recurrent-part-variants
- Owner: barricklab
- License: mit
- Created: 2023-04-07T21:57:01.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-04-20T17:36:48.000Z (over 3 years ago)
- Last Synced: 2025-09-09T13:54:10.377Z (11 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 448 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
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Analysis code for:
McGuffie, M.J., Barrick, J.E., 2023. __Identifying widespread and recurrent variants of genetic parts to improve annotation of engineered DNA sequences.__ https://doi.org/10.1101/2023.04.10.536277
This code uses a directory of CSVs generated by [pLannotate](https://github.com/barricklab/pLannotate) v1.2.0 from the Addgene plasmid database as input. The Addgene plasmid IDs used in analysis are available at [`data/addgene_ids.txt.gz`](./data/addgene_ids.txt.gz) in this repository. The associated plasmid sequences are available individually from the AddGene website (https://www.addgene.org/browse/) for download, and available for bulk download from AddGene upon request.
The computational enviroment can be created using the provided `env.yml` file with [conda](https://docs.conda.io/en/latest/) or [mamba](https://mamba.readthedocs.io/en/latest/installation.html). The environment can be created with the following command:
```bash
mamba env create -f env.yml
```
1. Annotate plasmids with pLannotate and output the results to a directory of CSVs.
2. Run `01_parsing_annotate_addgene_csvs.ipynb` to collect and clean the data.
3. Run `02_pairwise_ds_scores.py` to calculate DS scores of plasmid pairs.
4. Run `03_analyzing_clusters.ipynb` to cluster and analyze the part variants.
The output CSV of identified variants is available at [`data/supplemental_table_1.csv.gz`](./data/supplemental_table_1.csv.gz) in this repository.