Canu v2.1.1 + custom haplotype separation

Modifications and rationale

This fork contains basically two modifications in splitHapplotype.C, which performs classification of each child read into one of the two parents (or "unknwon"). There are three additional command-line arguments (run $ splitHaplotype for details):

1. min-kmer-freq in the -H argument

• By default, Canu automatically determines the minimum k-mer frequency used as a thoreshold for haplotype-specific k-mers for each parent read set based on the shape of the k-mer count histogram. However, it sometimes failes to detect appropriate thresholds especially when the input datasets have some problems (e.g. contamination). We added this argument so that a user can specify arbitrary thresholds determined by manual inspection of k-mer count histograms.

2. -M child-kmers.meryl min-kmer-freq

• This is used for ignoring k-mers that appear in the child dataset with a frequency smaller than some threshold, min-kmer-freq. K-mer counts of the child dataset, i.e. child-kmers.meryl, must be precomputed with Meryl provided in this repository.
• This removes potential false positive k-mer matches between child and parent datasets due to sequencing errors in child reads (Recall the spike around x=1 in the GenomeScope plot; we discard that part). This value should be determined by looking at the k-mer count histogram of the child dataset.

3. -cn number

• It requires each child read to have a difference in the number of k-mers shared with each of the two haplotypes greater than -cn in order to be classified. A larger threshold makes the decision of haplotype separation more conservative.

Currently these modifications are not incorporated into the whole pipeline of Canu but into only splitHaplotype, and one needs to use a custom script run_canu_haplotype.sh (put in the root directory of this branch) to run it.

how to install/use

1. Download and compile:

git clone https://github.com/yoshihikosuzuki/canu
cd canu/src
make -j<number of threads>

This will generate a directory named build/ in the root directory of this repository.

2. Modify the script run_canu_haplotype.sh (put in the root directory) according to your input files and environments and run it.

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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:

• The easiest way to get started is to download a binary release.

• 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

• 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>
  

• 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)