MEGAHIT is an ultra-fast and memory-efficient NGS assembler. It is optimized for metagenomes, but also works well on generic single genome assembly (small or mammalian size) and single-cell assembly.

conda install -c bioconda megahit

guix install megahit

wget https://github.com/voutcn/megahit/releases/download/v1.2.9/MEGAHIT-1.2.9-Linux-x86_64-static.tar.gz
tar zvxf MEGAHIT-1.2.9-Linux-x86_64-static.tar.gz
cd MEGAHIT-1.2.9-Linux-x86_64-static/bin/
./megahit --test  # run on a toy dataset
./megahit -1 MY_PE_READ_1.fq.gz -2 MY_PE_READ_2.fq.gz -o MY_OUTPUT_DIR

# in the directory with the input reads
docker run -v $(pwd):/workspace -w /workspace --user $(id -u):$(id -g) vout/megahit \
  megahit -1 MY_PE_READ_1.fq.gz -2 MY_PE_READ_2.fq.gz -o MY_OUTPUT_DIR

• For building: zlib, cmake >= 2.8, g++ >= 4.8.4
• For running: gzip and bzip2

git clone https://github.com/voutcn/megahit.git
cd megahit
git submodule update --init
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release  # add -DCMAKE_INSTALL_PREFIX=MY_PREFIX if needed
make -j4
make simple_test  # will test MEGAHIT with a toy dataset
# make install if needed

megahit -1 pe_1.fq -2 pe_2.fq -o out  # 1 paired-end library
megahit --12 interleaved.fq -o out # one paired & interleaved paired-end library
megahit -1 a1.fq,b1.fq,c1.fq -2 a2.fq,b2.fq,c2.fq -r se1.fq,se2.fq -o out # 3 paired-end libraries + 2 SE libraries
megahit_core contig2fastg 119 out/intermediate_contigs/k119.contig.fa > k119.fastg # get FASTG from the intermediate contigs of k=119

The contigs can be found final.contigs.fa in the output directory.

• --kmin-1pass: if sequencing depth is low and too much memory used when build the graph of k_min
• --presets meta-large: if the metagenome is complex (i.e., bio-diversity is high, for example soil metagenomes)
• --cleaning-rounds 1 --disconnect-ratio 0: get less pruned assembly (usually shorter contigs)
• --continue -o out: resume an interrupted job from out

To see the full manual, run megahit without parameters or with -h.

Also, our wiki may be helpful.

There is an example of a real assembly on this wiki page and its corresponding interactive Jupyter notebook. Contributed by Noah Lebovic (@lebovic).

• Li, D., Liu, C-M., Luo, R., Sadakane, K., and Lam, T-W., (2015) MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics, doi: 10.1093/bioinformatics/btv033 [PMID: 25609793].
• Li, D., Luo, R., Liu, C.M., Leung, C.M., Ting, H.F., Sadakane, K., Yamashita, H. and Lam, T.W., 2016. MEGAHIT v1.0: A Fast and Scalable Metagenome Assembler driven by Advanced Methodologies and Community Practices. Methods.

This project is licensed under the GPLv3 License - see the LICENSE file for details