Methods

Methods

What each step runs, with the exact settings that are not defaults.

Long reads

1. Trim (--trim-long): Porechop removes adapters (--check_reads 1000).
2. Filter (--filter-long): Filtlong keeps the best 95% of the bases (--keep_percent 95, --min_length 500); with --size, at most the best 100x of the genome (--target_bases).
3. Assemble: Flye (--nano-hq, 3 polishing iterations; expects recent super-accuracy basecalls) or Shasta (--config Nanopore-May2022, minimum read length 3,000 unless --min-size). The assembly graph is kept and drawn with Bandage; per-sample stats land in flye_stats.tsv / shasta_stats.tsv.
4. Polish, long reads: Medaka (medaka_consensus) with the model from --model. Pick the model that matches your flowcell/basecaller — a wrong model adds errors. --long-polisher none skips this (see Validation for measuring whether Medaka still helps on your basecalls).

Short reads (hybrid polishing)

5. Trim (--trim-short): fastp with a sliding-window quality cut (--cut_right, mean quality 10) and a 64 bp length floor; adapters auto-detected for pairs.
6. Polish, short reads: Polypolish (BWA -a all-alignments mapping of each mate, as its author specifies), then pyPOLCA with --careful. One Polypolish round only: a second round changed nothing in our tests. This pair was chosen because neither introduces errors in low-coverage regions — NextPolish, ntEdit and plain POLCA did, and were dropped. The final contigs are renamed contig_1, contig_2, …

Short reads only

• Assemble: SKESA (conservative, recommended for Illumina isolates) or SPAdes (scaffolds; --ion-torrent adds SPAdes' Ion Torrent mode; single-end supported by both). SKESA graphs are rebuilt with gfa_connector when it is installed.

QC (every run)

• QUAST over the final assemblies (--min-contig 1000).
• Qualimap bamqc per sample and read type, on a minimap2 mapping (map-ont or sr preset, unmapped reads dropped, duplicates removed with samtools markdup).
• Coverage: mean samtools depth over the final assembly, one table per read type.
• Dot plots: nucmer + mummerplot comparing the assembly before and after each polishing stage (raw vs Medaka, Medaka vs short-read polished) — a quick visual check that polishing did not rearrange anything.
• Assembly graphs: Bandage PNGs of the Flye/Shasta/SPAdes/gfa_connector graphs.

The version of every program used is written to log.txt in the output folder.

References

• Flye — Kolmogorov M, et al. Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol 37, 540–546 (2019).
• Shasta — Shafin K, et al. Nanopore sequencing and the Shasta toolkit enable efficient de novo assembly of eleven human genomes. Nat Biotechnol 38, 1044–1053 (2020).
• Medaka — Oxford Nanopore Technologies, https://github.com/nanoporetech/medaka
• Porechop — Wick RR, https://github.com/rrwick/Porechop
• Filtlong — Wick RR, https://github.com/rrwick/Filtlong
• SKESA (and gfa_connector) — Souvorov A, et al. SKESA: strategic k-mer extension for scrupulous assemblies. Genome Biol 19, 153 (2018). https://github.com/ncbi/SKESA
• SPAdes — Prjibelski A, et al. Using SPAdes de novo assembler. Curr Protoc Bioinformatics 70, e102 (2020).
• fastp — Chen S, et al. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).
• Polypolish — Wick RR, Holt KE. Polypolish: short-read polishing of long-read bacterial genome assemblies. PLoS Comput Biol 18, e1009802 (2022).
• pyPOLCA — Bouras G, et al. How low can you go? Short-read polishing of Oxford Nanopore bacterial genome assemblies. Microb Genom 10, 001254 (2024). POLCA: Zimin AV, Salzberg SL. PLoS Comput Biol 16, e1007981 (2020).
• BWA — Li H, Durbin R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
• minimap2 — Li H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).
• SAMtools — Danecek P, et al. Twelve years of SAMtools and BCFtools. GigaScience 10, giab008 (2021).
• QUAST — Gurevich A, et al. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29, 1072–1075 (2013).
• Qualimap — Okonechnikov K, et al. Qualimap 2. Bioinformatics 32, 292–294 (2016).
• MUMmer4 — Marçais G, et al. MUMmer4: a fast and versatile genome alignment system. PLoS Comput Biol 14, e1005944 (2018).
• Bandage — Wick RR, et al. Bandage: interactive visualization of de novo genome assemblies. Bioinformatics 31, 3350–3352 (2015).