This Nextflow pipeline performs automated plasmid assembly from PacBio long-read sequencing data using the Flye assembler as the core assembly engine. The pipeline implements a comprehensive workflow that includes read filtering, downsampling, assembly, consensus generation, circularization, annotation, and quality assessment.

The workflow follows a modular design with the following key components:

• Primary Assembler: Flye - optimized for long-read assembly of circular DNA elements
• Consensus Generation: Trycycler - creates high-quality consensus sequences from multiple assemblies
• Circularization: Circlator minimus2 - ensures proper circular contig formation
• Quality Control: Multi-stage filtering and validation

Length Range Filtering

• Reads length ranges from length_ranges.csv configuration file
• Applies size-based filtering to retain reads within specified ranges
• Helps remove very short fragments and excessive long reads that may impact assembly quality

Input Format

• Expects compressed FASTQ files (*fastq.gz) in the specified input directory
• Sample identification based on filename parsing

Downsampling

• Reduces read coverage to optimal levels for assembly
• Prevents computational bottlenecks while maintaining assembly quality
• Configurable coverage targets

Flye Assembly

• Utilizes Flye assembler specifically configured for plasmid assembly
• Optimized for circular DNA elements and repetitive sequences
• Generates initial contigs with associated assembly graphs

Contig Selection

• First selection step (SELECT_FA1) filters contigs based on length criteria
• Focuses on longer contigs likely to represent complete or near-complete plasmids

Circlator Processing

• Applies Circlator minimus2 to improve circular contig formation
• Corrects potential assembly breaks at circular junction points
• Essential for proper plasmid topology representation

Trycycler Integration

• Groups related contigs by sample identifier
• Generates high-quality consensus sequences
• Reconciles differences between multiple assembly attempts

Consensus Filtering

• Second selection step (SELECT_FA2) ensures quality consensus sequences
• Filters samples with excessive contig numbers that may indicate assembly issues

Plasmid Annotation

• Plannotate: Provides comprehensive plasmid-specific gene annotation
• Identifies resistance genes, replication origins, and other functional elements
• Generates GenBank format output for downstream analysis

Plasmid Mapping

• PlasmidMap: Creates visual representations of annotated plasmids
• Generates publication-ready circular maps

Assembly Metrics

• QUAST: Provides detailed assembly statistics and quality metrics
• Evaluates assembly completeness and accuracy

Read Alignment Analysis

• Minimap2: Aligns original reads back to assembled sequences
• PysamStats: Generates detailed alignment statistics and coverage analysis
• Replaces BAM read count analysis for improved accuracy

Comprehensive Reporting

• Summarize: Aggregates all metrics and statistics into final reports
• Combines alignment metrics with contig length information

• FASTQ Files: PacBio long-read sequencing data in compressed format
• Length Ranges: CSV file defining acceptable read length ranges

• params.input: Directory containing input FASTQ files
• Length filtering ranges defined in length_ranges.csv

The pipeline generates several categories of output:

• High-quality consensus plasmid sequences (FASTA)
• Circularized and polished contigs

• GenBank files with comprehensive gene annotations
• Functional element identification

• Assembly statistics and metrics
• Read alignment coverage analysis
• Comprehensive summary reports

• Circular plasmid maps
• Quality assessment plots

• Designed for parallel processing of multiple samples
• Memory requirements scale with genome size and read coverage
• Flye assembly is the most computationally intensive step

• Multi-stage filtering prevents low-quality assemblies from propagating
• Consensus generation improves final sequence accuracy
• Comprehensive quality metrics enable result validation

• Modular design allows for component replacement or modification
• Configurable parameters for different experimental conditions
• Supports batch processing of multiple plasmid samples

1. Accuracy: Combination of Flye assembly with Trycycler consensus generation
2. Completeness: Specific optimizations for circular plasmid assembly
3. Annotation: Integrated plasmid-specific gene annotation
4. Quality Control: Multiple validation and filtering steps
5. Automation: Fully automated workflow from raw reads to annotated assemblies
6. Scalability: Designed for high-throughput plasmid characterization

This pipeline provides a robust, automated solution for high-quality plasmid assembly from PacBio sequencing data, suitable for both research applications and routine plasmid characterization workflows.