Skill: metagenome-assembly

Use When

• The user wants to assemble metagenomic reads into contigs for downstream analysis.
• The user needs contigs for downstream binning and gene prediction.
• The user wants to compare assemblers (MEGAHIT vs metaSPAdes).
• The user has sufficient compute resources for de novo metagenomic assembly.

Inputs

• Required:
  • Host-depleted FASTQ file(s) (.fastq, .fq, .fastq.gz, .fq.gz).
• Optional:
  • --assembler STR — Assembler to use: megahit or metaspades (default: megahit).
  • --threads N — Number of threads (default: 4).
  • --memory N — Memory limit in GB (default: 16).
  • --min-length N — Minimum contig length in bp (default: 1000).
  • --kmer-sizes STR — Comma-separated k-mer sizes for metaSPAdes (e.g., 21,33,55,77).
  • --outdir DIR — Output directory (default: assembly_results).

Workflow

1. If MEGAHIT: run megahit with --min-contig-len, --num-cpu-threads, -m memory.
2. If metaSPAdes: run spades.py --meta with -k kmer sizes, -t threads, -m memory.
3. Filter contigs by minimum length.
4. Generate assembly statistics: total contigs, total length, N50, L50, largest contig, GC content.
5. Report assembly summary.

Output Contract

• Contigs FASTA — Assembled contigs filtered by minimum length (<outdir>/contigs_min<N>bp.fasta).
• Assembly statistics — N50, L50, total length, contig count, largest contig, GC percentage (<outdir>/assembly_stats.txt).

Limits

• metaSPAdes requires significantly more memory than MEGAHIT (100-500 GB vs 10-50 GB for human gut metagenomes).
• MEGAHIT is faster and more memory-efficient; recommended as the default for most samples.
• Minimum contig length of 1000 bp is recommended for downstream binning.
• Assembly quality depends heavily on sequencing depth and community complexity.
• MEGAHIT and metaSPAdes (SPAdes) must be installed and available on $PATH.
• This skill does not perform scaffolding; output is contigs only.
• Common failure cases:
  • metaSPAdes running out of memory on complex or deeply sequenced samples.
  • MEGAHIT crashing due to insufficient disk space for intermediate k-mer graph files.
  • Input reads still containing host contamination, inflating assembly size with host contigs.