This Jupyter notebook automates the retrieval of gene information from the NCBI Entrez Gene database using a list of gene IDs, processes the XML data, and integrates it with existing gene data stored in an Excel file. The fetched information is then merged with the Excel data, producing an updated version for further analysis or use.
- NCBI Entrez Gene API Integration: Retrieve up-to-date gene data such as gene name, status, description, and summary using a list of gene IDs.
- Error Handling with Retry Mechanism: Handles network and API errors by implementing exponential backoff and retries.
- Excel Data Integration: Merges the fetched gene data with an existing Excel dataset.
- Efficient XML Parsing: Extracts relevant information from the returned XML data in a structured manner.
- Python 3.x
- Required libraries:
pandas,tqdm,xml.etree.ElementTree,Bio(from Biopython for Entrez API),openpyxl(for handling Excel files)
Install the dependencies by running:
pip install pandas tqdm biopython openpyxlBefore running the notebook, ensure that the Excel file you're using is structured with the following columns:
| GeneID | Other_Column1 | Other_Column2 | ... |
|---|---|---|---|
| 1234 | Value1 | Value2 | ... |
| 5678 | Value3 | Value4 | ... |
The important column is GeneID, which should contain the numerical gene IDs that will be used to query the NCBI Entrez Gene database. Other columns can contain any additional data relevant to your analysis.
The updated Excel file will include the original data along with the new columns from the NCBI query, such as:
| GeneID | Gene Name | Status | Description | Summary |
|---|---|---|---|---|
| 1234 | GeneName1 | Active | Gene description here... | Summary of gene function... |
| 5678 | GeneName2 | Discontinued | Description... | Summary... |
- Provide a list of gene IDs (either manually or by reading from an Excel file).
- Execute the notebook, which will fetch data from the NCBI Entrez Gene API.
- The results will be merged with your existing Excel data and saved as
updated_osman.xlsx.
This project is licensed under the MIT License:
MIT License
Copyright (c) 2024 Felix Meier
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