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Human Genome Assembly in 100 Minutes

Chen-Shan ChiniD, Asif KhalakiD

Abstract

De novo genome assembly provides comprehensive, unbiased genomic information and makes it possible to gain insight into new DNA sequences not present in reference genomes. Many de novo human genomes have been published in the last few years, leveraging a combination of inexpensive short-read and single-molecule long-read technologies. As long-read DNA sequencers become more prevalent, the computational burden of generating assemblies persists as a critical factor. The most common approach to long-read assembly, using an overlap-layout-consensus (OLC) paradigm, requires all-to-all read comparisons, which quadratically scales in computational complexity with the number of reads. We assert that recently achievements in sequencing technology (i.e. with accuracy ~99% and read length ~10-15k) enables a fundamentally better strategy for OLC that is effectively linear rather than quadratic. Our genome assembly implementation, Peregrine uses sparse hierarchical minimizers (SHIMMER) to index reads thereby avoiding the need for an all-to-all read comparison step. Peregrine can assemble 30x human PacBio CCS read datasets in less than 30 CPU hours and around 100 wall-clock minutes to a high contiguity assembly (N50 > 20Mb). The continued advance of sequencing technologies coupled with the Peregrine assembler enables routine generation of human de novo assemblies. This will allow for population scale measurements of more comprehensive genomic variations -- beyond SNPs and small indels -- as well as novel applications requiring rapid access to de novo assemblies.

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Abstract summary

Verified abstract synthesis

Claude Opus 5.5 · xhigh effort · 18 Oct 2026 · from the abstract · CC BY-NC 4.0

Indexing long reads with sparse hierarchical minimizers removes the all-to-all comparison step, letting Peregrine assemble a 30x human PacBio CCS dataset in roughly 100 wall-clock minutes.

Overlap-layout-consensus (OLC) assembly of long reads needs every read compared with every other, so cost grows quadratically with read count and de novo human assembly stays expensive. The authors argue that reads at about 99% accuracy and 10-15k length let the overlap stage be restructured as an effectively linear one, putting routine human de novo assembly within reach.

Key results

  1. SuggestedA human assembly finishes in about 100 minutes of wall-clock time while staying highly contiguous.

    A 30x human PacBio CCS dataset assembled in under 30 CPU hours, around 100 wall-clock minutes, reaching N50 > 20Mb; no comparison against other assemblers is reported. · Abstract

  2. ClaimedThe speed comes from replacing all-to-all read comparison with a minimizer index, which the authors argue turns the overlap stage from quadratic into effectively linear scaling.

    Peregrine indexes reads using sparse hierarchical minimizers (SHIMMER), skipping the pairwise comparison step that standard OLC requires; the linear behaviour is asserted for reads at roughly 99% accuracy and 10-15k length, without a scaling measurement. · Abstract

  3. ClaimedCheap routine assembly is presented as opening up population-scale study of variation that SNP and small-indel calling misses.

    Stated as a consequence of combining improving sequencers with this assembler; no population-scale analysis is carried out in the abstract. · Abstract

Methods, data and reproducibility

Peregrine is a long-read assembler that indexes reads with sparse hierarchical minimizers (SHIMMER), so the pairwise comparison of every read against every other that standard overlap-layout-consensus assembly performs is avoided. It was run on a 30x human PacBio CCS dataset and assessed on CPU hours, wall-clock time and contig N50.

  • Human PacBio CCS long-read dataset used for the assembly benchmark · human · n = 30x coverage
Methods & tools
Peregrine, SHIMMER (sparse hierarchical minimizers), PacBio CCS
Assay conditions & compute
Under 30 CPU hours and about 100 wall-clock minutes for the human assembly; the machine, core count and memory are not stated.
Limitations (2)
  • Timing and contiguity come from one 30x human CCS dataset, with no competing assembler run for comparison on either runtime or assembly quality. · noted in this summary
  • The shift from quadratic to linear behaviour is asserted rather than measured: no scaling curve across read counts is shown, and assembly correctness (base accuracy, misassemblies) is not reported alongside N50. · noted in this summary

Who should read:Read this if you assemble long-read genomes and want to know how far minimizer-based indexing can cut the overlap stage, or need human de novo assemblies at population scale.

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