Awesome
Canu
Canu is a fork of the Celera Assembler, designed for high-noise single-molecule sequencing (such as the PacBio RS II/Sequel or Oxford Nanopore MinION).
Canu is a hierarchical assembly pipeline which runs in four steps:
- Detect overlaps in high-noise sequences using MHAP
- Generate corrected sequence consensus
- Trim corrected sequences
- Assemble trimmed corrected sequences
Install:
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Do NOT download the .zip source code. It is missing files and will not compile. This is a known flaw with git itself.
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The easiest way to get started is to download a binary release.
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Installing with a 'package manager' is not encouraged, but if you have no other choice:
- Conda:
conda install -c conda-forge -c bioconda -c defaults canu
- Homebrew:
brew install brewsci/bio/canu
- Conda:
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Alternatively, you can use the latest unreleased version from the source code. This version has not undergone the same testing as a release and so may have unknown bugs or issues generating sub-optimal assemblies. We recommend the release version for most users.
git clone https://github.com/marbl/canu.git cd canu/src make -j <number of threads>
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FreeBSD generally requires libboost be installed from packages/ports. It will compile with either clang (>= 14) or gcc (>= 9). It requires openjdk18.
With clang, (default 14) needs libboost from ports. gmake With gcc (9+), can use the canu-supplied libboost or libboost from ports. gmake CC=gcc9 CXX=g++9 BOOST=libboost # Canu-supplied boost gmake CC=gcc9 CXX=g++9 # Ports/packages supplied boost
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MacOS Apple Silicon requires libboost, and either openjdk or oracle-jdk to be installed from homebrew (preferred) or MacPorts. It will compile with either clang (>=14) or gcc (>= 9) but WILL NOT compile with the standard Xcode compiler.
make CC=gcc-11 CXX=g++-11 BOOST=libboost # Ports/packages supplied boost make CC=gcc-11 CXX=g++-11 # Ports/packages supplied boost
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MacOS Intel is probably the same as Apple Silicon, but not tested.
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Linux does not need a system installed libboost.
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An unsupported Docker image made by Frank Förster is at https://hub.docker.com/r/greatfireball/canu/.
Learn:
The quick start will get you assembling quickly, while the tutorial explains things in more detail.
Run:
Brief command line help:
../<architecture>/bin/canu
Full list of parameters:
../<architecture>/bin/canu -options
Citation:
- Koren S, Walenz BP, Berlin K, Miller JR, Phillippy AM. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Research. (2017).
doi:10.1101/gr.215087.116
- Koren S, Rhie A, Walenz BP, Dilthey AT, Bickhart DM, Kingan SB, Hiendleder S, Williams JL, Smith TPL, Phillippy AM. De novo assembly of haplotype-resolved genomes with trio binning. Nature Biotechnology. (2018). (If you use trio-binning)
- Nurk S, Walenz BP, Rhiea A, Vollger MR, Logsdon GA, Grothe R, Miga KH, Eichler EE, Phillippy AM, Koren S. HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads. biorXiv. (2020). (If you use -pacbio-hifi)