NOTE: This is under active development, any feedback will be very useful
🐉 🪰 Assemble bacterial isolate genomes from Nanopore reads
If you've worked with bacterial sequences, in all likelihood you have used one of Torsten Seemann's tools. One such tool is Shovill, which takes the bacterial genome assembly process and makes it quick and painless. Shovill was developed for paired-end Illumina reads, and there is a fork, shovill-se, which supports single-end reads.
Given the widespread usage of Shovill, and Torsten basically laying much of the groundwork, I decided to use Shovill as a framework for Dragonflye. Dragonflye can be considered a fork of Shovill that supports assembling Oxford Nanopore sequences. By going this route users will not have to relearn parameters, and will already be familiar with the outputs.
At this point, you might be wondering: so Robert you just hacked Shovill to work with ONT reads, why not just call it 'shovill-ont'?
That's because when I asked if there was interest in a "Shovill" for ONT reads, Curtis Kapsak (@kapsakcj) responded:
Curtis Kapsak (@kapsakcj): if wrapping
flye
, perhaps call itdragonflye
(a very fast flye)?.
And, honestly how could I not go with that?!? It's an amazing play-on-words that I'm willing to bet Torsten would be proud of it!
So to sum it up, thank you Torsten for Shovill and providing a framework for Dragonflye.
Dragonflye is a pipeline that aims to make assembling Oxford Nanopore reads quick and easy. Still working on the quick part, but I think the easy part is there. Dragonflye currently supports Flye, Miniasm and Raven assemblers, and Racon and Medaka polishers.
- Estimate genome size and read length from reads (unless
--gsize
provided) (kmc) - Filter reads by length (default
--minreadlength 1000
) (Nanoq) - Reduce FASTQ files to a sensible depth (default
--depth 150
) (rasusa) - Remove adapters (requires
--trim
be given) (Porechop) - Assemble with Flye, Miniasm, or Raven
- Polish assembly with Racon and/or Medaka
- Polish assembly with short reads via Polypolish and/or Pilon
- Remove contigs that are too short, too low coverage, or pure homopolymers
- Produce final FASTA with nicer names and parsable annotations
- Output parsable assembly statistics (assembly-scan)
dragonflye --reads my-ont.fastq.gz --outdir dragonflye --gsize 5000000
... LOG TEXT ...
[dragonflye] Final assembly contigs: /home/robert_petit/repos/dragonflye/temp/dragonflye/contigs.fa
[dragonflye] It contains 3 (min=4864) contigs totalling 4939840 bp.
[dragonflye] Dragonfly fossils have been found with wingspans up to two feet (61cm)!
[dragonflye] Done.
ls dragonflye/
contigs.fa contigs.gfa dragonflye.log flye-info.txt flye.fasta
head -n4 dragonfly/contigs.fa
>contig00001 len=4818942 cov=62.0 corr=0 origname=contig_1 sw=dragonflye-flye/0.0.1 date=20210720 circular=Y
TTAATTTGATGCCTGGCAGTTCCCTACTCTCGCATGGGGAGACCCCACACTACCATCGGC
GCTACGGCGTTTCACTTCTGAGTTCGGCATGGGGTCAGGTGGGACCACCGCGCTAAGGCC
GCCAGGCAAATTCTGTTTTATCAGACCGCTTCTGCGTTCTGATTTAATCTGTATCAGGCT
Dragonflye is available from Bioconda. Dragonflye includes a lot of programs, so it can take conda
a
while to solve the environment. Because of this, I personally use Mamba
to install it, because it's so much faster.
# With conda
conda create -n dragonflye -c conda-forge -c bioconda dragonflye
# With Mamba (much quicker)
mamba create -n dragonflye -c conda-forge -c bioconda dragonflye
Dragonflye - A very fast flye
SYNOPSIS
De novo assembly pipeline for bacterial isolates with Nanopore reads
USAGE
dragonflye [options] --outdir DIR --reads READS.fastq.gz
GENERAL
--help This help
--version Print version and exit
--check Check dependencies are installed
--seed N Random seed to use (default: 42)
INPUT
--reads XXX Input Nanopore FASTQ (default: '')
--depth N Sub-sample --reads to this depth. Disable with --depth 0 (default: 150)
--minreadlen N Minimum read length. Disable with --minreadlength 0 (default: 1000)
--gsize XXX Estimated genome size eg. 3.2M <blank=AUTODETECT> (default: '')
OUTPUT
--outdir XXX Output folder (default: '')
--force Force overwite of existing output folder (default: OFF)
--minlen N Minimum contig length <0=AUTO> (default: 500)
--mincov n.nn Minimum contig coverage <0=AUTO> (default: 2)
--namefmt XXX Format of contig FASTA IDs in 'printf' style (default: 'contig%05d')
--keepfiles Keep intermediate files (default: OFF)
RESOURCES
--tmpdir XXX Fast temporary directory (default: '')
--cpus N Number of CPUs to use (0=ALL) (default: 8)
--ram n.nn Try to keep RAM usage below this many GB (default: 16)
ASSEMBLER
--assembler XXX Assembler: raven miniasm flye (default: 'flye')
--opts XXX Extra assembler options in quotes eg. flye: '--interations' (default: '')
--nanohq For Flye, use '--nano-hq' instead of --nano-raw (default: OFF)
POLISHER
--racon N Number of polishing rounds to conduct with Racon (default: 1)
--medaka N Number of polishing rounds to conduct with Medaka (requires --model) (default: 0)
--model XXX The model to be used by Medaka, (Assumes 1 polishing round, if --medaka not used) (default: '')
--list_models List the models available to Medaka (default: OFF)
SHORT-READ POLISHER
--polypolish N Number of polishing rounds to conduct with Polypolish (requires --R1 and --R2) (default: 1)
--pilon N Number of polishing rounds to conduct with Pilon (requires --R1 and --R2) (default: 0)
--R1 XXX Read 1 FASTQ to use for polishing (default: '')
--R2 XXX Read 2 FASTQ to use for polishing (default: '')
MODULES
--trim Enable adaptor trimming (default: OFF)
--trimopts XXX Extra porechop options in quotes eg. '--adapter_threshold 80' (default: '')
--nofilter Disable read length filtering (default: OFF)
--nopolish Disable assembly polishing (default: OFF)
HOMEPAGE
https://github.com/rpetit3/dragonflye - Robert A Petit III
Giving an assembler too much data is a bad thing. There comes a point where you are no longer adding new information (as the genome is a fixed size), and only adding more noise (sequencing errors). Because of this Dragonflye will downsample your FASTQ files to a specific depth (defaults to 150x). It estimates depth by dividing read yield by genome size.
The genome size is needed to estimate depth and for the assembly stage. If you don't provide --gsize
,
it will be estimated via k-mer frequencies using kmc
. It doesn't need to be a perfect estimate,
just in the right ballpark. If you know the genome size it is usually better then the estimate,
and will save some time.
This will keep all the intermediate files in --outdir
so you can explore and debug.
By default it will attempt to use all available CPU cores.
Dragonflye will do its best to keep memory usage below this value, but it is not guaranteed. If you are on a HPC cluster, you should make sure you tell your job submission engine a value higher than this.
By default it will use FlyeA.
If you want to provide some assembler-specific parameters you can use the --opts
parameter. Make sure you quote the parameters so they get passed as a single string
eg. For --assembler flye
you might use --opts "--iterations 4 --plasmids"
.
These two parameters adjust how many polishing rounds are conducted per-polisher. For example,
--racon 2
would conduct 2 rounds of polishing with Racon. If --medaka
is provided, a model
must also be provided with --model
.
A valid basecaller model must be provided with --model
. If a valid model is provided, but
--medaka
was not provided it will assume --medaka 1
.
This will list all basecaller models that are avialable in Medaka.
If Illumina short-reads are provided, polishing will be done with Polypolish and/or Pilon. The value of --polypolish
(Default 1) is the number
of polishing rounds that will be conducted. By default Pilon is turned off.
Stage | Enable | Disable |
---|---|---|
Genome size estimation | default | --gsize INT |
Read subsampling | --depth INT |
--depth 0 |
Read length filtering | default | --nofilter |
Adapter Trimming | --trim |
default |
These env-vars will be used as defaults instead of the built-in defaults. You can use the normal command line option to override them still.
Variable | Option | Default |
---|---|---|
$DRAGONFLYE_CPUS |
--cpus |
8 |
$DRAGONFLYE_RAM |
--ram |
16 |
$DRAGONFLYE_ASSEMBLER |
--assembler |
flye |
$TMPDIR |
--tmpdir |
/tmp |
Filename | Description |
---|---|
contigs.fa |
The final assembly you should use |
contigs.gfa |
Assembly graph |
dragonflye.log |
Full log file for bug reporting |
flye.fasta |
Raw assembly (flye) |
flye-info.txt |
Information about contigs output by Flye |
miniasm.fasta |
Raw assembly (miniasm) |
raven.fasta |
Raw assembly (raven) |
-
Perl?!?! Perl?!? Really, why Perl?
Dragonflye is a fok of Shovill, and Shovill was written in Perl. Haha so yeah, instead of writing from scratch, I dusted off the old Perl skills. Upon which the Perl interpretor basically told me I sucked at Perl every time I tried to make a change (haha kept forgetting the semi-colons at the end of the line!).
-
Does
dragonflye
accept Illumina reads?No, this is strictly for Nanopore reads only. If you want to assemble Illumina reads, use Shovill.
-
Doesn't Trycycler already do this?
Dragonflye is not trying to replicate Trycycler, Trycycler is on a whole 'nother level. If you are looking to get super high quality assemblies with some manual inspection steps in between, use Trycycler. But, if you are looking to just get a quick assembly that you can work with, that's what Dragonfly is for.
-
Can I use my GPU during the Medaka step?
Yes, you can! As of v1.0.8,
tensorflow-gpu
is included in the Bioconda recipe. This should allow you to use your GPU with Medaka. There might be environment variables you have to set, to learn more please take a look here: issues/7#issuecomment-1054693716
Please file questions, bugs or ideas to the Issue Tracker
I would like to personally extend my many thanks and gratitude to the authors of these software packages. Really, thank you very much!
-
any2fasta
Convert various sequence formats to FASTA
Seemann, T any2fasta: Convert various sequence formats to FASTA. -
assembly-scan
Generate basic stats for an assembly.
Petit III, RA assembly-scan: generate basic stats for an assembly. -
BWA
Burrow-Wheeler Aligner for short-read alignment
Li, H Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv [q-bio.GN] (2013) -
fastp
An ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting/merging...)
Chen, S, Zhou, Y, Chen, Y, Gu, J, fastp: an ultra-fast all-in-one FASTQ preprocessor, Bioinformatics, Volume 34, Issue 17 (2018) -
Flye
De novo assembler for single molecule sequencing reads using repeat graphs
Kolmogorov, M, Yuan, J, Lin, Y, Pevzner, P, Assembly of Long Error-Prone Reads Using Repeat Graphs, Nature Biotechnology, (2019) -
KMC
Fast and frugal disk based k-mer counter
Deorowicz, S, Kokot, M, Grabowski, Sz, Debudaj-Grabysz, A, KMC 2: Fast and resource-frugal k-mer counting, Bioinformatics, 2015; 31(10):1569–1576 -
Medaka
Sequence correction provided by ONT Research
Li, H Medaka: Sequence correction provided by ONT Research -
Miniasm
Ultrafast de novo assembly for long noisy reads (though having no consensus step)
Li, H Miniasm: Ultrafast de novo assembly for long noisy reads -
Minimap2
A versatile pairwise aligner for genomic and spliced nucleotide sequences
Li, H Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics, 34:3094-3100. (2018) -
Nanoq
Minimal but speedy quality control for nanopore reads in Rus
Steinig, E Nanoq: Minimal but speedy quality control for nanopore reads in Rus -
Pigz
A parallel implementation of gzip for modern multi-processor, multi-core machines.
Adler, M pigz: A parallel implementation of gzip for modern multi-processor, multi-core machines. Jet Propulsion Laboratory (2015). -
Pilon
An automated genome assembly improvement and variant detection tool
Walker, BJ, Abeel, T, Shea, T, Priest, M, Abouelliel, A, Sakthikumar, S, Cuomo, CA, Zeng, Q, Wortman, J, Young, SK, Earl, AM, Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PloS one 9.11 e112963 (2014) -
Polypolish
A short-read polishing tool for long-read assemblies
Wick, RR, Holt, KE, Polypolish: Short-read polishing of long-read bacterial genome assemblies. PLoS Computational Biology, 18(1), e1009802. (2022) -
Porechop
Adapter trimmer for Oxford Nanopore reads
Wick, RR, Judd, LM, Gorrie, CL, Holt, KE, Completing bacterial genome assemblies with multiplex MinION sequencing. Microb Genom. 3(10):e000132 (2017) -
Racon
Ultrafast consensus module for raw de novo genome assembly of long uncorrected reads
Vaser, R, Sović, I, Nagarajan, N, Šikić, M, Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res. 27, 737–746 (2017). -
Rasusa
Randomly subsample sequencing reads to a specified coverage
Hall, MB Rasusa: Randomly subsample sequencing reads to a specified coverage. (2019). -
Raven
De novo genome assembler for long uncorrected reads
Vaser, R, Šikić, M Time- and memory-efficient genome assembly with Raven. Nat Comput Sci 1, 332–336 (2021). -
samclip
Filter SAM file for soft and hard clipped alignments
Seemann, T Samclip: Filter SAM file for soft and hard clipped alignments (GitHub) -
Samtools
Tools for manipulating next-generation sequencing data
Li, H, Handsaker, B, Wysoker, A, Fennell, T, Ruan, J, Homer, N, Marth, G, Abecasis, G, Durbin, R The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009) -
Seqtk
A fast and lightweight tool for processing sequences in the FASTA or FASTQ format.
Li, H Seqtk: Toolkit for processing sequences in FASTA/Q formats
- Robert A. Petit III
- Web: https://www.robertpetit.com
- Twitter: @rpetit3