PCR-bias

This repository contains the code and data associated with the study:

Deep learning uncovers sequence-specific amplification bias in multi-template PCR

It includes scripts for deep learning model validation and motif discovery, aiming to analysis sequence-specific biases that arise during PCR amplification.

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Contents

• CluMo.py
  A Python script that implements the motif discovery approach introduced in the study.

• InternalValidation.py
  Performs 5-fold internal validation on the selected dataset.

• ExternalValidation.py
  Performs external validation on the selected dataset and evaluate all other datasets to measure generalization.

• analysis/
  Contains additional scripts/notebooks for analyzing results and generating figures for the manuscript.

• utils/
  Utility functions for data loading, preprocessing, model construction, and training.

• Data/
  DNA sequence dataset with binarization of PCR efficiency under different thresholds.

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Dependencies

The software is implemented using Python 3.9.7.

All major dependencies can be found in requirements.txt.

You can install these packages by running:

python -m pip install pip==23.2.1
pip install -r requirements.txt

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Quick Demo

Running motif discovery

python CluMo.py --filename dataset

The results will be saved under CNN/motifs/{dataset}/{threshold}/

Running internal and external validation

python InternalValidation(ExternalValidation).py --filename dataset

The results will be saved under CNN/results/interal(external)/{dataset}/{threshold}/

The dataset should be specified as one of the 7 datasets used in this study: `

• "Choi_et_al",
• "Erlich_et_al",
• "Gao_et_al",
• "GCall",
• "GCfix",
• "Koch_et_al",
• "Song_et_al" `

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Citation

Please use the following to cite our work:

@article{gimpel2024deep,
  title={Deep learning uncovers sequence-specific amplification bias in multi-template PCR},
  author={Gimpel, Andreas L and Fan, Bowen and Chen, Dexiong and W{\"o}lfle, Laetitia OD and Horn, Max and Meng-Papaxanthos, Laetitia and Antkowiak, Philipp L and Stark, Wendelin J and Christen, Beat and Borgwardt, Karsten and others},
  journal={bioRxiv},
  pages={2024--09},
  year={2024},
  publisher={Cold Spring Harbor Laboratory}
}