Flye

Flye assembles genomes de novo from single-molecule long reads (PacBio and Oxford Nanopore Technologies) to produce polished contigs for genomic analyses.

Key Features:

• Long-Read Assembly: Assembles PacBio and Oxford Nanopore Technologies (ONT) long reads to resolve repetitive regions and improve contiguity.
• Repeat Graph Construction: Generates disjointigs from error-prone long reads and constructs a repeat graph to resolve repeats and increase assembly quality, with reported NGA50 improvements for human assemblies.
• Hybrid Assembly Capabilities: Integrates long-read data with Illumina short reads for hybrid assemblies to enhance accuracy and completeness, demonstrated on bacterial genomes including Enterobacteriaceae.
• Polishing and Output: Processes raw PB/ONT reads and outputs polished contigs as the final assembly product.
• Automation and Efficiency: Provides an automated pipeline for de novo assembly of raw long reads into contigs.
• Metagenomic Assembly (metaFlye): Extends Flye for long-read metagenomic datasets (metaFlye), addressing uneven bacterial composition and intra-species heterogeneity to reconstruct complete or near-complete genomes.

Scientific Applications:

• Bacterial Genome Assembly: Reconstructs high-quality bacterial genomes for studies of complex genetic structures and antimicrobial resistance, including applications to Enterobacteriaceae.
• Human and Microbiome Genomics: Improves contiguity in human genome assemblies and enables resolution of full-length biosynthetic gene clusters in microbiome studies.
• Metagenomic Studies: Assembles complex microbial communities from long-read metagenomic datasets using metaFlye to recover complete or nearly complete bacterial genomes.

Methodology:

Generates disjointigs from error-prone long reads; constructs a repeat graph for repeat resolution; supports hybrid assembly by integrating Illumina short reads with long reads; outputs polished contigs; metaFlye adapts the approach for uneven composition and intra-species heterogeneity in metagenomic datasets.