Redundans pipeline assists an assembly of heterozygous genomes.
Program takes as input assembled contigs, sequencing libraries and/or reference sequence and returns scaffolded homozygous genome assembly. Final assembly should be less fragmented and with total size smaller than the input contigs. In addition, Redundans will automatically close the gaps resulting from genome assembly or scaffolding.
The pipeline consists of several steps (modules):
- de novo contig assembly (optional if no contigs are given)
- redundancy reduction: detection and selective removal of redundant contigs from an initial de novo assembly
- scaffolding: joining of genome fragments using paired-end reads, mate-pairs, long reads and/or reference chromosomes
- gap closing: filling the gaps after scaffolding using paired-end and/or mate-pair reads
Redundans is:
- fast & lightweight, multi-core support and memory-optimised, so it can be run even on the laptop for small-to-medium size genomes
- flexible toward many sequencing technologies (Illumina, 454, Sanger, PacBio & Nanopore) and library types (paired-end, mate pairs, fosmids, long reads)
- modular: every step can be omitted or replaced by other tools
- reliable: it has been already used to improve genome assemblies varying in size (several Mb to several Gb) and complexity (fungal, animal & plants)
For more information have a look at the documentation, poster, publication, test dataset or manual.
Redundans uses several programs (all provided within this repository):
- Platanus
- LAST v800+
- BWA v0.7.12+
- SNAP aligner
- SSPACE3
- GapCloser
- pyScaf
- FastaIndex
On most Linux distros, the installation should be as easy as:
git clone --recursive https://github.com/lpryszcz/redundans.git
cd redundans && bin/.compile.sh
If it fails, make sure you have below dependencies installed:
- Python 2.7 or 2.6
- Perl [SSPACE3]
- make, gcc & g++ [BWA & LAST] ie.
sudo apt-get install make gcc g++
- zlib including zlib.h headers [BWA] ie.
sudo apt-get install zlib1g-dev
- optionally for plotting
numpy
andmatplotlib
ie.sudo -H pip install -U matplotlib numpy
For user convenience, we provide UNIX installer and Docker image, that can be used instead of manually installation.
UNIX installer will automatically fetch, compile and configure Redundans together with all dependencies. It should work on all modern Linux systems, given Python 2.7, commonly used programmes (ie. wget, curl, git, perl, gcc, g++, ldconfig) and libraries (zlib including zlib.h) are installed.
source <(curl -Ls http://bit.ly/redundans_installer)
First, you need to install docker: wget -qO- https://get.docker.com/ | sh
Then, you can run the test example by executing:
# process the data inside the image - all data will be lost at the end
docker run -it -w /root/src/redundans lpryszcz/redundans ./redundans.py -v -i test/{600,5000}_{1,2}.fq.gz -f test/contigs.fa -o test/run1
# if you wish to process local files, you need to mount the volume with -v
## make sure you are in redundans repo directory (containing test/ directory)
docker run -v `pwd`/test:/test:rw -it lpryszcz/redundans /root/src/redundans/redundans.py -v -i test/*.fq.gz -f test/contigs.fa -o test/run1
Docker images are very handy, but they have certain limitation. The most annoying for me is the lack of autocompletion, unless you specify the path in host and container in the exactly same manner as in the example above. In addition, the volume needs to be mounted every time, leading to a bit complex commands.
Redundans input consists of any combination of:
- assembled contigs (FastA)
- paired-end and/or mate pairs reads (FastQ*)
- long reads (FastQ/FastA*) - both PacBio and Nanopore are supported
- and/or reference chromosomes/contigs (FastA).
- gzipped files are also accepted.
Redundans will return homozygous genome assembly in scaffolds.filled.fa
(FastA).
In addition, the program reports statistics for every pipeline step, including number of contigs that were removed, GC content, N50, N90 and size of gap regions.
For the user convenience, Redundans is equipped with a wrapper that automatically estimates run parameters and executes all steps/modules.
You should specify some sequencing libraries (FastA/FastQ) or reference sequence (FastA) in order to perform scaffolding.
If you don't specify -f
contigs (FastA), Redundans will assemble contigs de novo, but you'll have to provide paired-end and/or mate pairs reads (FastQ).
Most of the pipeline parameters can be adjusted manually (default values are given in square brackets []):
HINT: If you run fails, you may try to resume it, by adding --resume
parameter.
- General options:
-h, --help show this help message and exit
-v, --verbose verbose
--version show program's version number and exit
-i FASTQ, --fastq FASTQ
FASTQ PE / MP files
-f FASTA, --fasta FASTA
FASTA file with contigs / scaffolds
-o OUTDIR, --outdir OUTDIR
output directory [redundans]
-t THREADS, --threads THREADS
no. of threads to run [4]
--resume resume previous run
--log LOG output log to [stderr]
--nocleaning
- Reduction options:
--identity IDENTITY min. identity [0.51]
--overlap OVERLAP min. overlap [0.80]
--minLength MINLENGTH
min. contig length [200]
--noreduction Skip reduction
- Short-read scaffolding options:
-j JOINS, --joins JOINS
min pairs to join contigs [5]
-a LINKRATIO, --linkratio LINKRATIO
max link ratio between two best contig pairs [0.7]
--limit LIMIT align subset of reads [0.2]
-q MAPQ, --mapq MAPQ min mapping quality [10]
--iters ITERS iterations per library [2]
--noscaffolding Skip short-read scaffolding
- Long-read scaffolding options:
-l LONGREADS, --longreads LONGREADS
FastQ/FastA files with long reads
--identity IDENTITY min. identity [0.51]
--overlap OVERLAP min. overlap [0.80]
- Reference-based scaffolding options:
-r REFERENCE, --reference REFERENCE
reference FastA file
--norearrangements high identity mode (rearrangements not allowed)
--identity IDENTITY min. identity [0.51]
--overlap OVERLAP min. overlap [0.80]
- Gap closing options:
--iters ITERS iterations per library [2]
--nogapclosing
Redundans is extremely flexible. All steps of the pipeline can be ommited using: --noreduction
, --noscaffolding
and/or --nogapclosing
parameters.
To run the test example, execute:
./redundans.py -v -i test/*_?.fq.gz -f test/contigs.fa -o test/run1
# if your run failed for any reason, you can try to resume it
rm test/run1/_sspace.2.1.filled.fa
./redundans.py -v -i test/*_?.fq.gz -f test/contigs.fa -o test/run1 --resume
# if you have no contigs assembled, just run without `-f`
./redundans.py -v -i test/*_?.fq.gz -o test/run.denovo
Note, the order of libraries (-i/--input
) is not important, as long as read1
and read2
from each library are given one after another
i.e. -i 600_1.fq.gz 600_2.fq.gz 5000_1.fq.gz 5000_2.fq.gz
would be interpreted the same as -i 5000_1.fq.gz 5000_2.fq.gz 600_1.fq.gz 600_2.fq.gz
.
You can play with any combination of inputs ie. paired-end, mate pairs, long reads and / or reference-based scaffolding, for example:
# reduction, scaffolding with paired-end, mate pairs and long reads, and gap closing with paired-end and mate pairs
./redundans.py -v -i test/*_?.fq.gz -l test/pacbio.fq.gz test/nanopore.fa.gz -f test/contigs.fa -o test/run_short_long
# scaffolding and gap closing with paired-end and mate pairs (no reduction)
./redundans.py -v -i test/*_?.fq.gz -f test/contigs.fa -o test/run_short-scaffolding-closing --noreduction
# reduction, reference-based scaffolding and gap closing with paired-end reads (--noscaffolding disables only short-read scaffolding)
./redundans.py -v -i test/600_?.fq.gz -r test/ref.fa -f test/contigs.fa -o test/run_ref_pe-closing --noscaffolding
For more details have a look in test directory.
If you have any issues or doubts check documentation and FAQ (Frequently Asked Questions). You may want also to sign to our forum.
Leszek P. Pryszcz and Toni Gabaldón (2016) Redundans: an assembly pipeline for highly heterozygous genomes. NAR. doi: 10.1093/nar/gkw294