| name | megahit |
| description | Ultra-fast memory-efficient metagenome assembler. Use this skill when working with megahit: installing, choosing parameters, running commands, interpreting outputs, or troubleshooting. Upstream: https://github.com/voutcn/megahit. For routing across tools, use tool-selection. For end-to-end pipelines, use metagenomics-workflow.
|
| license | MIT |
| category | analysis-tools |
| tags | ["assembly","contigs"] |
| upstream | https://github.com/voutcn/megahit |
MEGAHIT
Upstream: voutcn/megahit (v1.2.9 widely used)
Citation
Li, D., Liu, C.-M., Luo, R., Sadakane, K. & Lam, T.-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676 (2015). https://doi.org/10.1093/bioinformatics/btv033
See also docs/references.md.
Analytical thinking
MEGAHIT is the default fast metagenome assembler for Illumina PE when memory
or turnaround time dominate. Co-assembly increases shared-genome continuity but
can smear strains—decide with study-design first.
Always evaluate assemblies (QUAST) before gene calling or binning. Delete
intermediate_contigs after success to save disk.
Prerequisites
| Requirement | Minimum | Recommended |
|---|
| Input | Dehosted PE | From kneaddata |
| RAM | 32 GB small | 128–512 GB co-assemblies |
| CPU | 8 | 32+ |
How to run
conda install -c bioconda megahit
megahit --test
megahit -t 32 \
-1 s1_1.fastq,s2_1.fastq \
-2 s1_2.fastq,s2_2.fastq \
-o temp/megahit
Single sample: -1/-2 one pair. Output contigs: temp/megahit/final.contigs.fa.
Key parameters
| Parameter | Notes |
|---|
-t | Threads |
--min-contig-len | Raise to shrink huge contig sets before binning |
-o | Must not exist (delete to rerun) |
Decision tree
Need contigs quickly with moderate memory?
├─ Yes → megahit
├─ Need max continuity, can pay RAM/time → metaspades
└─ Long reads dominant → long-read assembler (not megahit alone)
Related skills
metaspades · prodigal · metawrap · basalt · study-design
