URAdime 0.1.1

Universal Read Analysis of DIMErs

URAdime

URAdime (Universal Read Analysis of DIMErs) is a Python package for analyzing primers in BAM files. It provides tools for identifying and analyzing primer sequences in DNA sequencing data.

Installation

pip install uradime

Usage

URAdime can be used both as a command-line tool and as a Python package.

Command Line Interface

# Basic usage
uradime -b input.bam -p primers.tsv -o results/my_analysis

# Full options
uradime \
    -b input.bam \                    # Input BAM file
    -p primers.tsv \                  # Primer file (tab-separated)
    -o results/my_analysis \          # Output prefix
    -t 8 \                           # Number of threads
    -m 1000 \                        # Maximum reads to process (0 for all)
    -c 100 \                         # Chunk size for parallel processing
    -u \                             # Process only unaligned reads
    --max-distance 2 \               # Maximum Levenshtein distance for matching
    -v                               # Verbose output

Python Package

from uradime import bam_to_fasta_parallel, create_analysis_summary, load_primers

# Load and analyze BAM file
result_df = bam_to_fasta_parallel(
    bam_path="your_file.bam",
    primer_file="primers.tsv",
    num_threads=4
)

# Load primers for analysis
primers_df, _ = load_primers("primers.tsv")

# Create analysis summary
summary_df, matched_pairs, mismatched_pairs = create_analysis_summary(result_df, primers_df)

Input Files

Primer File Format (TSV)

The primer file should be tab-separated with the following columns:

• Name: Primer pair name
• Forward: Forward primer sequence
• Reverse: Reverse primer sequence
• Size: Expected amplicon size

Example:

Name    Forward             Reverse             Size
Pair1   ATCGATCGATCG       TAGCTAGCTAGC       100
Pair2   GCTAGCTAGCTA       CGATTCGATCGA       150

Output Files

The tool generates several CSV files with the analysis results:

• *_summary.csv: Overall analysis summary
• *_matched_pairs.csv: Reads with matching primer pairs
• *_mismatched_pairs.csv: Reads with mismatched primer pairs
• *_wrong_size_pairs.csv: Reads with correct primer pairs but wrong size

Features

• BAM file analysis
• Primer sequence identification
• Flexible matching with Levenshtein distance
• Comprehensive analysis reporting
• Parallel processing support
• Both CLI and Python API

Requirements

• Python ≥3.7
• pysam
• pandas
• biopython
• python-Levenshtein
• tqdm
• numpy

License

This project is licensed under the MIT License - see the LICENSE file for details.