Flye is a de novo assembler for long and noisy reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is built on top of the ABruijn assembler, and features many new algorithmic improvements. The core read overlapping algorithm uses an A-Bruijn graph to find the mappings between reads and does not require them to be error-corrected. As a result, Flye is 2-10 times faster then hierarchical assembly pipelines. After the initial contig assembly, Flye constructs assembly (repeat) graph and accurately resolves repeats using bridging reads. The package also includes a polisher module, which produces the final assembly of high nucleotide-level quality.
- Improvements in repeat edges detection
- More precise read mapping - more contigious assemblies for some datasets
- Memory and performance optimizations for high-coverage datasets
- More accurate repeat graphs for complex datasets
Experimental Flye version for metagenome assembly is available in the 'flye-meta' branch of this repository. Be aware that this is still an early 'beta' version, and the code is frequently updated.
- Memory consumption for large genome assemblies reduced by ~30%
- It could be reduced even further by using the new option --asm-coverage, which specifies a subset of reads for initial contig assembly
- Better repeat graph representation for complex genomes
- Various bugfixes and stability improvements
- ABruijn 2.x branch has been renamed to Flye, highlighting many substantial algorithmic changes
- Stable version of the repeat analysis module
- New command-line syntax (fallback mode with the old syntax is available)
- New --subassemblies mode for generating consensus of multiple assemblies
- Improved preformance and reduced memory footprint (now scales to human genome)
- Corrected reads are now supported
- Extra output with information about the contigs (coverage, multiplicity, graph paths etc.)
- Gzipped Fasta/q support
- Multiple read files support
- Various bugfixes
The Flye algorithms are operating on the assembly (repeat) graph. The edges in this graph represent genomic sequences, and nodes simply serve as junctions. The genoimc chromosomes traverse this graph (in an unknown way) so as each unique edge is covered exactly once. The genomic repeats that were not resolved are collapsed into the corresponding edges in the graph (therefore genome structure remain umbigious).
An example of a final assembly graph of a bacterial genome is above. Each edge is labeled with its id, length and coverage. Repetitive edges are shown in color, while unique edges are black. The clusters of adjacent repeats are shown with the same color. Note that each edge is represented in two copies: forward and reverse complement (marked with +/- signs), therefore the entire genome is represented in two copies as well. Sometimes (as in this example), forward and reverse-complement components are clearly separated, but often they form a single connected component (in case if the genome contain unresolved inverted repeats).
In this example, there are two unresolved repeats: (i) a red repeat of multiplicity two and length 35k and (ii) a green repeat cluster of multiplicity three and length 34k - 36k. As the repeats remained unresolved, there are no reads in the dataset that cover those repeats in full.
Flye package includes some third-party software:
Flye is distributed under a BSD license. See the LICENSE file for details.
Flye was developed in Pavel Pevzner's lab at UCSD
Code contributions:
- Original assembler code: Yu Lin
- Original polisher code: Jeffrey Yuan
- Repeat graph and current package support: Mikhail Kolmogorov
Mikhail Kolmogorov, Jeffrey Yuan, Yu Lin and Pavel Pevzner, "Assembly of Long Error-Prone Reads Using Repeat Graphs", bioRxiv, 2018
Yu Lin, Jeffrey Yuan, Mikhail Kolmogorov, Max W Shen, Mark Chaisson and Pavel Pevzner, "Assembly of Long Error-Prone Reads Using de Bruijn Graphs", PNAS, 2016
Please report any problems to the github issue tracker (at http://github.com/fenderglass/Flye). If possible, please include "flye.log" file from the output directory for faster feedback. Alternatively, you can write directly to [email protected].