- Enhanced zmw_selector.py: Refined the original script to improve efficiency and functionality.
- New run_zmw_selector.sh: Added a shell script for streamlined execution of the Python script, including environment setup and error detection.
This repository contains the refined zmw_selector.py
script and the newly added run_zmw_selector.sh
script for enhanced functionality and efficiency in extracting Pacific Bioscience's Zero-Mode Waveguides (ZMWs) near predicted transcription factor binding sites. The original script is credited to the Ramani Lab's SAMOSA project.
- Automatic BAM Indexing: The script now checks for the existence of a BAM index file. If none exists or if the existing index is outdated, the script generates a new index file based on the BAM file's creation date.
- Improved Error Handling: Added comprehensive error handling to manage various edge cases and ensure robust script execution.
- Refactored Code: Simplified and cleaned the code for better readability and maintainability.
- Environment Setup: The shell script activates a Conda environment linked to a Jupyter kernel, ensuring all required packages are available.
- Error Detection: Implemented echo statements within the shell script to identify and report potential errors, aiding in quick troubleshooting.
- Batch Processing: Allows the user to pass a directory of BAM files, processing each file sequentially and outputting individual ZMW TSV files.
- Conda installed and configured.
- Jupyter Notebook installed.
- Required Python packages listed in
zmw_selector_updated.py
import section (provided in the repository).