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12. De Novo Genome & Transcriptome Assembly

⚡ Category 12 of 14  ·  🧬 7 Primary Tools

Reconstructing complete genomes and transcriptomes without a reference scaffold using De Bruijn graphs, overlap-layout-consensus (OLC), and diploid phased assembly.

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12. De Novo Genome & Transcriptome Assembly

7 Primary Tools

Reconstructing contigs and chromosome-level scaffolds without a reference genome, followed by consensus error correction and base polishing.

ToolPrimary Role & PurposeSupported PlatformsExecutable Pipeline
SPAdes / metaSPAdes →Multi-sized de Bruijn graph assembler for small genomes and metagenomesShort-Read & HybridView Code ↓
MEGAHIT →Memory-efficient de Bruijn graph assembler for large metagenomic setsMetagenomic Short ReadsView Code ↓
Flye →Repeat graph assembler for Oxford Nanopore and PacBio dataLong-Read (ONT / PacBio)View Code ↓
Hifiasm →Leading de novo assembler for PacBio HiFi and HiFi+Trio/Hi-C dataPacBio HiFi / Hi-C / TrioView Code ↓
Canu →Overlap-Layout-Consensus (OLC) assembler for noisy long readsONT / PacBio CLRView Code ↓
Medaka →Neural network model polishing consensus sequences from ONT alignmentsOxford Nanopore DraftsView Code ↓
Racon / Pilon →Fast consensus module (Racon for long reads; Pilon for short-read polishing)Hybrid Assembly PolishingView Code ↓
🌐 Extended Assembly, Scaffolding & Polishing Ecosystem: Long & Short-Read Genomes
Long-Read Assemblers: Flye, hifiasm, Verkko, Canu, Shasta, Raven, NECAT
Short-Read Assemblers: SPAdes, MEGAHIT, SOAPdenovo2, ABySS
Scaffolding & Hi-C: YaHS, SALSA2, 3D-DNA, Juicebox Assembly Tools
Polishing & QC: Medaka, Racon, Pilon, DeepPolisher, QUAST, BUSCO, Merqury, compleasm
Annotation & Repeats: BRAKER3, MAKER, Funannotate, RepeatMasker, EDTA
Pangenome Graphs: minigraph-cactus, PGGB, vg toolkit
♠️

Multi-k-mer de Bruijn Graph Bacterial & Metagenomic Assembly

Iterative Multi-k-mer Isolates & Plasmids

SPAdes is the benchmark de novo assembler for bacterial, fungal, and viral genomes. It employs iterative multi-sized de Bruijn graphs and read error correction to produce contigs and scaffold graphs, with dedicated modes for plasmids and metagenomes.

# 1. Run SPAdes bacterial genome assembly with multi-k-mer iteration
spades.py \
  -1 sample_R1.fastq.gz -2 sample_R2.fastq.gz \
  -k 21,33,55,77,99,127 \
  --careful \
  --threads 16 \
  --memory 64 \
  -o spades_isolate_out/

# Output contigs: spades_isolate_out/contigs.fasta
# Output scaffolds: spades_isolate_out/scaffolds.fasta
Key Flags: --careful runs mismatch post-correction to reduce false indels; -k 21,33,55,77,99,127 builds multi-sized de Bruijn graphs to span repetitive loci.
⚡

Ultra-Fast Low-Memory Metagenomic Assembler

Low Memory Succinct de Bruijn

MEGAHIT assembles complex, large-scale metagenomic datasets using succinct de Bruijn graphs. It consumes minimal memory and scales smoothly to terabyte-scale FASTQ archives without requiring massive supercomputing nodes.

# 1. Assemble metagenomic paired-end reads with succinct de Bruijn graph
megahit \
  -1 sample_R1.fq.gz -2 sample_R2.fq.gz \
  --k-list 21,29,39,59,79,99,119,141 \
  --min-contig-len 500 \
  -m 0.85 \
  -t 24 \
  -o megahit_assembly/

# Final contigs: megahit_assembly/final.contigs.fa
Key Flags: --k-list progresses through iterative k-mer steps; -m 0.85 caps maximum RAM at 85% available system memory.
🪰

Repeat Graph De Novo Assembly for Long Reads

Repeat Graph Chromosome Scale

Flye is a de novo assembler for single-molecule sequencing reads using repeat graphs. It resolves complex structural genomic repeats, assembling complete circular bacterial chromosomes and eukaryotic chromosome arms from ONT and PacBio data.

# 1. Assemble Oxford Nanopore long reads
flye \
  --nano-hq ont_reads.fq.gz \
  --genome-size 5m \
  --out-dir flye_assembly/ \
  --threads 16 \
  --iterations 2

# Output assembly: flye_assembly/assembly.fasta
# Assembly graph (GFA): flye_assembly/assembly_graph.gfa
Key Flags: --nano-hq (or --pacbio-hifi) specifies read type; --iterations 2 performs consensus polishing rounds.
🧬

Haplotype-Resolved De Novo PacBio HiFi Assembler

Haplotype Resolved PacBio HiFi Gold

Hifiasm produces haplotype-resolved, chromosome-level de novo genome assemblies from PacBio HiFi reads. When provided with Hi-C or parental trio data, it phases both maternal and paternal haplotypes end-to-end without reference bias.

# 1. Haplotype-resolved assembly with PacBio HiFi reads and Hi-C pairs
hifiasm \
  -o asm_sample \
  -t 24 \
  --h1 hic_R1.fq.gz --h2 hic_R2.fq.gz \
  pacbio_hifi.fastq.gz

# 2. Extract phased FASTA contigs from GFA graphs
awk '/^S/{print ">"$2"\n"$3}' asm_sample.hic.hap1.p_ctg.gfa > hap1_contigs.fasta
awk '/^S/{print ">"$2"\n"$3}' asm_sample.hic.hap2.p_ctg.gfa > hap2_contigs.fasta
Key Flags: --h1 --h2 integrates Hi-C contact pairs for chromosome-wide phasing; extracts maternal (hap1) and paternal (hap2) haplotypes.
📐

Overlap-Layout-Consensus (OLC) Noisy Long-Read Assembler

OLC Paradigm Error Correction

Canu is an Overlap-Layout-Consensus assembler designed for noisy single-molecule reads. It executes automated read self-correction with MinHash alignment (MHAP), read trimming, and unitig generation.

# 1. Run end-to-end Canu assembly on Oxford Nanopore reads
canu \
  -p sample_asm -d canu_out/ \
  genomeSize=4.8m \
  maxThreads=16 \
  -nanopore ont_reads.fq.gz
Key Flags: genomeSize=4.8m supplies expected haploid genome length for coverage calculation; -nanopore tunes overlap error thresholds.
🧠

Neural Network Model Consensus Polishing for Nanopore

Neural Polishing ONT Official

Medaka is a consensus tool developed by Oxford Nanopore. It aligns ONT reads to draft assemblies and uses recurrent neural networks to resolve remaining insertion/deletion errors and homopolymer run ambiguities.

# 1. Polish draft assembly with chemistry-specific neural network model
medaka_consensus \
  -i ont_reads.fq.gz \
  -d draft_assembly.fasta \
  -o medaka_polished/ \
  -t 16 \
  -m r1041_e82_400bps_sup_v4.2.0

# Polished consensus in: medaka_polished/consensus.fasta
Key Flags: -m r1041_e82_400bps_sup_v4.2.0 loads neural network weights corresponding to the basecaller chemistry used; -t 16 sets worker threads.
✨

Long-Read SIMD Consensus & Short-Read Base Polishing

SIMD Consensus Illumina Polishing

Racon rapidly computes consensus sequences using SIMD-accelerated partial order alignment. Pilon then aligns high-accuracy paired-end Illumina reads to the draft assembly to fix single-base substitution errors and indels.

# 1. Fast long-read consensus polishing with Racon
minimap2 -t 16 draft.fasta ont_reads.fq.gz > ont_to_draft.paf
racon -t 16 ont_reads.fq.gz ont_to_draft.paf draft.fasta > racon_polished.fasta

# 2. Map high-accuracy short reads to consensus
bwa index racon_polished.fasta
bwa mem -t 16 racon_polished.fasta illumina_R1.fq.gz illumina_R2.fq.gz \
  | samtools sort -@ 4 -o illumina_to_draft.sorted.bam -
samtools index illumina_to_draft.sorted.bam

# 3. Final base-error polishing with Pilon
pilon --genome racon_polished.fasta \
  --frags illumina_to_draft.sorted.bam \
  --output pilon_final_polished \
  --vcf --changes
Key Flags: racon -t 16 executes partial-order alignment graph consensus; pilon --changes logs all single-base substitutions and indel fixes.
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