Releases: mikolmogorov/Flye
Releases · mikolmogorov/Flye
Flye 2.7.1
- Fixes very long GFA generation time for some large assemblies (no other changes)
Flye v2.7
- Better assemblies of real (and comlpex) metagenomes
- New option to retain alternative haplotypes, rather than collapsing them (
--keep-haplotypes
) - PacBio HiFi mode
- Using Bam instead of Sam to reduce storage requirements and IO load
- Improved human assemblies
- Annotation of alternative contigs
- Better polishing quality for the newest ONT datasets
- Trestle module is disabled by default (use
--trestle
to enable) - Many big fixes and improvements
Flye 2.6
- This release introduces Python 3 support (no other functional changes)
Flye 2.5
- Better ONT polishing for the latest basecallers (Guppy/flipflop)
- Improved consensus quality of repetitive regions
- More contigouous assemblies of real metagenomes
- Improvements for human genome assemblies
- Various bugfixes and performance optimizations
Flye 2.4.2
- Improvements in k-mer selection and tip clipping for metagenome assemblies
- Better memory managment during consensus/polishing
- Some bugfixes
Flye 2.4.1
- Speed and stability improvements for large datasets
- New option
--polish-target
to run Flye polisher on the target sequence
Flye 2.4
- Metagenome assembly support fully integrated (
--meta
option) - New Trestle module for resolving simple unbridged repeats
- New
--plasmids
option that recovers short unassmbled plasmids
Flye 2.3.7
- Improvements in repeat edges detection
- More precise read mapping - more contiguous assemblies for some datasets
- Memory and performance optimizations for high-coverage datasets
- More accurate repeat graphs for complex datasets
Flye 2.3.6
- 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
Flye 2.3.5
- New read mapping implementation (based on solid k-mers) with improved specificity
- Better support of corrected reads input
- Minimum read overlap is now selected within a wider range for better support of datasets with shorter read length
- Assembly of large (human size) genomes is now faster
- Various bugfixes and stability improvements