CUTPLASMID is a comprehensive tool designed for the identification and analysis of PAM (Protospacer Adjacent Motif) sequences in genome data, crucial for CRISPR-Cas systems. This script processes genomic data, identifies PAM sequences, and provides detailed statistical and visual analyses, including heatmaps and machine learning-based classification reports.
- Data Preprocessing: Supports raw data filtering using
fastp
. - PAM Sequence Counting: Counts upstream and downstream PAM sequences around a target sequence.
- Heatmap Generation: Creates heatmaps to visualize PAM sequence distributions.
- Machine Learning: Trains and evaluates models to classify significant PAM sequences.
- Visualization: Generates various plots and logos to represent PAM sequence statistics and distributions.
Ensure the following dependencies are installed:
- Python 3.6+
- pandas
- numpy
- argparse
- datetime
- itertools
- gzip
- json
- seaborn
- Bio (Biopython)
- scipy
- sklearn
- matplotlib
- fastp
- weblogo
Install dependencies using pip:
pip install pandas numpy argparse datetime biopython scipy scikit-learn matplotlib seaborn
- Clone the repository:
git clone https://github.com/yourusername/CUTPLASMID.git
cd CUTPLASMID
- Ensure you have
fastp
andweblogo
installed and available in your PATH.
Argument | Description |
---|---|
-e, --experiment |
The experiment data file, separated by commas (required) |
-c, --control |
The control data file, separated by commas (required) |
-o, --output |
The output directory (required) |
-t, --target |
The target sequence (required) |
-u, --upstream |
The upstream PAM library length (default: 4) |
-d, --downstream |
The downstream PAM library length (default: 4) |
-f, --fastp |
Use fastp to filter the raw data (optional) |
-sd, --seqDirection |
The sequence direction of the PAM (forward or reverse , default: forward ) |
-hm, --heatmap |
Draw the heatmap of the PAM count (optional) |
-kt, --keeptmp |
Keep the temporary files (optional) |
python cutplasmid.py -e experiment1.fastq,experiment2.fastq -c control1.fastq,control2.fastq -o ./output -t AGGCTAGC -u 4 -d 4 -f -hm
This tool was developed by Chen QI, Baitao LI, and collaborators from BNU-HKBU United International College, University of Chinese Academy of Sciences, and BGI Research.
For any questions or support, please contact [qichen@uic.edu.cn].