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PySNV v1.0.0 - Release for "PySNV for complex intra-host variation detection" paper

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@bnuLyndon bnuLyndon released this 17 Mar 07:40
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PySNV v1.0.0 - Release for "PySNV for complex intra-host variation detection" paper

This release corresponds to the version of PySNV described in the paper "PySNV for complex intra-host variation detection" published in Bioinformatics (2024).

About PySNV

PySNV is a Python-based software tool for detecting complex intra-host variation from tNGS data.

Requirements

Ensure you have the following Python libraries installed:

  1. numpy
  2. pandas
  3. psutil
  4. Bio
  5. hirola
  6. scipy

Python Usage

  1. Download and unzip the project code
  2. Modify the running_dir variable in example.py to set the running directory.
  3. Set the sample file(s) and genome file in example.py.
  4. Run example.py.

Example Files

  • example.py: Demonstrates basic usage of the PySNV tool.
  • detect_sample.py: Main function of processing for a single sample.
  • example_multi_files.py: Illustrates how to process multiple input files simultaneously. Paired samples should include '_R1' and '_R2' in the file names. Adjust the number of kernels to use parallel processing.
  • detect_sample.py: Main function of processing for a sample folder.

Note: Before running the examples, make sure to set the necessary parameters in the file.

Bash Usage

Command

python detect_sample.py --sample1 path/to/sample1.fastq --sample2 path/to/sample2.fastq --reference path/to/reference_genome.fa --output output_filename

Parameters

  • --sample1: Path to single-end sample or first paired-end sample. Fasta, fastq and gz files are supported.
  • --sample2 (optional): Path to the second paired-end sample.
  • --reference (required): Path to the reference genome.
  • --output: Output file path and name (default is current working directory, using sample name as output filename).

Additional Parameters

  • --threshold: Detection Threshold (Default: 0.02)
    • The recommended detection threshold should be larger than the sequencing error rate.
  • --kmer_length: Kmer Length (Default: 21)
    • This parameter specifies the length of k-mers to be considered during the analysis and must be an odd number smaller than 31. Kmer length should be set to ensure no duplicate kmer exists on the genome.
  • --downsample: Downsample Factor (Default: 1)
    • Downsampling of sequencing reads could enhance detection speed and reduce RAM usage, which could be used for high-depth sequencing samples.
  • --error_rate: Sequencing Error Rate (Default: 0.01)
    • Used to filter out possible false positive detection.
  • --indel_limit: Maximum Indel Length (Default: 300)
    • To mitigate false positive indels, especially in the case of challenging long insertions and potential impacts on estimated sequencing depths due to long deletions, a default maximum indel length of 300 is set. The recommended length threshold is 2*average_read_length.

Citation

If you use PySNV in your research, please cite the following paper:

Li, L., Fu, H., Ma, W., & Li, M. (2024). PySNV for complex intra-host variation detection. Bioinformatics, btae116.

Support

For any questions, issues, or feature requests, please open a new issue on the PySNV GitHub repository.

License

PySNV is released under the MIT License.

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