DAJIN2 0.3.5

One-step genotyping tools for targeted long-read sequencing

日本語はこちら

DAJIN2 is a genotyping software designed for organisms that have undergone genome editing, utilizing nanopore sequencing technology.

The name DAJIN is inspired by the term 一網打尽 (Ichimou DAJIN or Yīwǎng Dǎjìn), which signifies capturing everything in a single net.

🛠 Installation

Prerequisites

• Python 3.7 or later
• Unix-like environment (Linux, macOS, WSL2, etc.)

From Bioconda (Recommended)

conda install -c bioconda DAJIN2

From PyPI

pip install DAJIN2

[!CAUTION] If you encounter any issues during the installation, please refer to the Troubleshooting Guide

💡 Usage

Single Sample Analysis

DAJIN2 allows for the analysis of single samples (one sample vs one control).

DAJIN2 <-s|--sample> <-c|--control> <-a|--allele> <-n|--name> \
  [-g|--genome] [-t|--threads] [-h|--help] [-v|--version]

options:
  -s, --sample              Path to a sample FASTQ file
  -c, --control             Path to a control FASTQ file
  -a, --allele              Path to a FASTA file
  -n, --name                Output directory name
  -g, --genome (Optional)   Reference genome ID (e.g hg38, mm39) [default: '']
  -t, --threads (Optional)  Number of threads [default: 1]
  -h, --help                show this help message and exit
  -v, --version             show the version number and exit

Example

# Donwload the example dataset
wget https://github.com/akikuno/DAJIN2/raw/main/examples/example-single.tar.gz
tar -xf example-single.tar.gz

# Run DAJIN2
DAJIN2 \
    --name stx2-deletion \
    --sample example-single/sample.fq.gz \
    --control example-single/control.fq.gz \
    --allele example-single/design.fa \
    --genome mm39 \
    --threads 10

# 2023-06-04 11:30:03: example-single/control.fq.gz is now processing...
# 2023-06-04 11:30:06: Preprocess example-single/control.fq.gz...
# 2023-06-04 11:30:06: Mapping example-single/control.fq.gz...
# 2023-06-04 11:30:21: Call MIDSV example-single/control.fq.gz...
# 2023-06-04 11:30:31: 🍵 example-single/control.fq.gz is finished!
# 2023-06-04 11:30:31: example-single/sample.fq.gz is now processing...
# 2023-06-04 11:30:35: Preprocess example-single/sample.fq.gz...
# 2023-06-04 11:34:13: Classify example-single/sample.fq.gz...
# 2023-06-04 11:34:18: Clustering example-single/sample.fq.gz...
# 2023-06-04 11:35:01: Consensus calling example-single/sample.fq.gz...
# 2023-06-04 11:35:08: 🍵 example-single/sample.fq.gz is finished!
# 🎉 Finished! Open DAJIN_Results/stx2-deletion to see the report.

Batch Processing

By using the batch subcommand, you can process multiple FASTQ files simultaneously.
For this purpose, a CSV or Excel file consolidating the sample information is required.
For a specific example, please refer to this link.

DAJIN2 batch <-f|--file> [-t|--threads] [-h]

options:
  -f, --file                Path to a CSV or Excel file
  -t, --threads (Optional)  Number of threads [default: 1]
  -h, --help                Show this help message and exit

Example

# Donwload the example dataset
wget https://github.com/akikuno/DAJIN2/raw/main/examples/example-batch.tar.gz
tar -xf example-batch.tar.gz

# Run DAJIN2
DAJIN2 batch --file example-batch/batch.csv --threads 3

# 2023-07-31 17:01:10: example-batch/tyr_control.fq.gz is now processing...
# 2023-07-31 17:01:16: Preprocess example-batch/tyr_control.fq.gz...
# 2023-07-31 17:01:48: Output BAM files of example-batch/tyr_control.fq.gz...
# 2023-07-31 17:01:52: 🍵 example-batch/tyr_control.fq.gz is finished!
# 2023-07-31 17:01:52: example-batch/tyr_c230gt_50%.fq.gz is now processing...
# 2023-07-31 17:01:52: example-batch/tyr_c230gt_10%.fq.gz is now processing...
# 2023-07-31 17:01:52: example-batch/tyr_c230gt_01%.fq.gz is now processing...
# 2023-07-31 17:01:55: Preprocess example-batch/tyr_c230gt_01%.fq.gz...
# 2023-07-31 17:01:55: Preprocess example-batch/tyr_c230gt_50%.fq.gz...
# 2023-07-31 17:01:55: Preprocess example-batch/tyr_c230gt_10%.fq.gz...
# 2023-07-31 17:02:17: Classify example-batch/tyr_c230gt_50%.fq.gz...
# 2023-07-31 17:02:19: Clustering example-batch/tyr_c230gt_50%.fq.gz...
# 2023-07-31 17:02:34: Classify example-batch/tyr_c230gt_01%.fq.gz...
# 2023-07-31 17:02:35: Classify example-batch/tyr_c230gt_10%.fq.gz...
# 2023-07-31 17:02:39: Clustering example-batch/tyr_c230gt_01%.fq.gz...
# 2023-07-31 17:02:39: Clustering example-batch/tyr_c230gt_10%.fq.gz...
# 2023-07-31 17:02:53: Consensus calling of example-batch/tyr_c230gt_50%.fq.gz...
# 2023-07-31 17:02:59: Output reports of example-batch/tyr_c230gt_50%.fq.gz...
# 2023-07-31 17:03:04: 🍵 example-batch/tyr_c230gt_50%.fq.gz is finished!
# 2023-07-31 17:03:39: Consensus calling of example-batch/tyr_c230gt_01%.fq.gz...
# 2023-07-31 17:03:51: Output reports of example-batch/tyr_c230gt_01%.fq.gz...
# 2023-07-31 17:04:03: 🍵 example-batch/tyr_c230gt_01%.fq.gz is finished!
# 2023-07-31 17:04:08: Consensus calling of example-batch/tyr_c230gt_10%.fq.gz...
# 2023-07-31 17:04:16: Output reports of example-batch/tyr_c230gt_10%.fq.gz...
# 2023-07-31 17:04:24: 🍵 example-batch/tyr_c230gt_10%.fq.gz is finished!
# 🎉 Finished! Open DAJIN_Results/tyr-substitution to see the report.

📈 Report Contents

Upon completion of DAJIN2 processing, a directory named DAJIN_Results is generated.
Inside the DAJIN_Results directory, the following files can be found:

DAJIN_Results/tyr-substitution
├── BAM
│   ├── tyr_c230gt_01%
│   ├── tyr_c230gt_10%
│   ├── tyr_c230gt_50%
│   └── tyr_control
├── FASTA
│   ├── tyr_c230gt_01%
│   ├── tyr_c230gt_10%
│   └── tyr_c230gt_50%
├── HTML
│   ├── tyr_c230gt_01%
│   ├── tyr_c230gt_10%
│   └── tyr_c230gt_50%
├── MUTATION_INFO
│   ├── tyr_c230gt_01%.csv
│   ├── tyr_c230gt_10%.csv
│   └── tyr_c230gt_50%.csv
├── read_all.csv
├── read_plot.html
├── read_plot.pdf
└── read_summary.csv

1. BAM

The BAM directory contains the BAM files of reads classified per allele.

[!NOTE] Specifying a reference genome using the genome option will align the reads to that genome.
Without genome options, the reads will align to the control allele within the input FASTA file.

2. FASTA and HTML

The FASTA directory stores the FASTA files of each allele.
The HTML directory contains HTML files for each allele, where mutation sites are color-highlighted.
For example, Tyr point mutation is highlighted in green.

3. MUTATION_INFO

The MUTATION_INFO directory saves tables depicting mutation sites for each allele.
An example of a Tyr point mutation is described by its position on the chromosome and the type of mutation.

4. read_plot.html and read_plot.pdf

Both read_plot.html and read_plot.pdf illustrate the proportions of each allele.
The chart's Allele type indicates the type of allele, and % of reads shows the proportion of reads for that allele.

Additionally, the types of Allele type include:

• intact: Alleles that perfectly match the input FASTA allele.
• indels: Substitutions, deletions, insertions, or inversions within 50 bases.
• sv: Substitutions, deletions, insertions, or inversions beyond 50 bases.

[!WARNING] In PCR amplicon sequencing, the % of reads might not match the actual allele proportions due to amplification bias.
Especially when large deletions are present, the deletion alleles might be significantly amplified, potentially not reflecting the actual allele proportions.

5. read_all.csv and read_summary.csv

• read_all.csv: Records which allele each read is classified under.
• read_summary.csv: Describes the number of reads and presence proportion for each allele.

📄 References

For more information, please refer to the following publication:

Kuno A, et al. (2022) DAJIN enables multiplex genotyping to simultaneously validate intended and unintended target genome editing outcomes. PLoS Biology 20(1): e3001507.

📣Feedback and Support

For questions, bug reports, or other forms of feedback, we'd love to hear from you!
Please use GitHub Issues for all reporting purposes.

Please refer to CONTRIBUTING for how to contribute and how to verify your contributions.

🤝 Code of Conduct

Please note that this project is released with a Contributor Code of Conduct.
By participating in this project you agree to abide by its terms.