extracTR 0.2.8

Extract and analyze satellite DNA from raw sequences.

extracTR

Introduction

extracTR is a powerful tool for extracting and analyzing tandem repeats from raw DNA sequences. It utilizes advanced algorithms to identify repetitive patterns in genomic data, providing valuable insights for researchers in genomics and bioinformatics.

Features

• Efficient tandem repeat detection from raw sequencing data
• Support for paired-end FASTQ files
• Customizable parameters for fine-tuning repeat detection
• Output in easy-to-analyze CSV format
• Multi-threaded processing for improved performance

Requirements

• Python 3.7 or later
• Jellyfish 2.3.0 or later
• Conda (for easy environment management)

Installation

We recommend installing extracTR in a separate Conda environment to manage dependencies effectively.

1. Create a new Conda environment:

conda create -n extractr_env python=3.9

2. Activate the environment:

conda activate extractr_env

3. Install Jellyfish:

conda install -c bioconda jellyfish

4. Install extracTR using pip:

pip install extracTR

To deactivate the environment when you're done:

conda deactivate

Usage

Before running extracTR, ensure that you have removed adapters from your sequencing reads and activated the Conda environment:

conda activate extractr_env

Basic usage:

extracTR -1 reads_1.fastq -2 reads_2.fastq -o output_prefix

Advanced usage with custom parameters:

extracTR -1 reads_1.fastq -2 reads_2.fastq -o output_prefix -t 64 -c 30 -k 25

Options:

• -1, --fastq1: Input file with forward DNA sequences in FASTQ format
• -2, --fastq2: Input file with reverse DNA sequences in FASTQ format
• -o, --output: Prefix for output files
• -t, --threads: Number of threads to use (default: 32)
• -c, --coverage: Coverage to use for indexing (default: 1)
• -k, --k: K-mer size to use for indexing (default: 23)

Output

extracTR generates the following output files:

• {output_prefix}.csv: Main output file containing detected tandem repeats
• {output_prefix}.sdat: Intermediate file with k-mer frequency data
• Additional files for detailed analysis and debugging