Evaluating genome assemblies with HMM-Flagger

HMM-Flagger is a reference-free tool for detecting structural errors in haplotype-resolved genome assemblies based upon the coverage of mapped reads. It models read coverage with a hidden Markov model augmented by a Gaussian autoregressive process, which enables classifying coverage anomalies as erroneous blocks, false duplications, or collapsed blocks. Trained and tested on synthetic misassemblies, it detected synthetic errors using Pacific Biosciences HiFi and Oxford Nanopore Technologies R10 data with F1 scores of 78.4% and 60.4% respectively. When applied to six HG002 assemblies it revealed multiple large misassemblies including false duplications and collapse events in human satellites. Applied to assemblies from the Human Pangenome Reference Consortium (HPRC), HMM-Flagger demonstrated substantial improvements from release 1 (0.94% error rate) to release 2 (0.38%), reflecting technological advances. HMM-Flagger also validated NOTCH2NL assemblies in HPRC release 2 and confirmed the correctness of three novel structural configurations.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-03-02
DOI
https://doi.org/10.64898/2026.02.27.708355
Primary Topic
Genomics and Phylogenetic Studies
Type
article
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article

Evaluating genome assemblies with HMM-Flagger

Taylor Real, Julian Lucas, Sofie Salama, Jordan M. Eizenga et al.
bioRxiv (Cold Spring Harbor Laboratory)
Genomics and Phylogenetic Studies
article

Evaluating genome assemblies with HMM-Flagger

Taylor Real, Julian Lucas, Sofie Salama, Jordan M. Eizenga, Prajna Hebbar, Alessandro Calicchio, Mobin Asri, Hailey Loucks, Karen H Miga, Benedict Paten, Evan E Eichler
article en

Abstract

HMM-Flagger is a reference-free tool for detecting structural errors in haplotype-resolved genome assemblies based upon the coverage of mapped reads. It models read coverage with a hidden Markov model augmented by a Gaussian autoregressive process, which enables classifying coverage anomalies as erroneous blocks, false duplications, or collapsed blocks. Trained and tested on synthetic misassemblies, it detected synthetic errors using Pacific Biosciences HiFi and Oxford Nanopore Technologies R10 data with F1 scores of 78.4% and 60.4% respectively. When applied to six HG002 assemblies it revealed multiple large misassemblies including false duplications and collapse events in human satellites. Applied to assemblies from the Human Pangenome Reference Consortium (HPRC), HMM-Flagger demonstrated substantial improvements from release 1 (0.94% error rate) to release 2 (0.38%), reflecting technological advances. HMM-Flagger also validated NOTCH2NL assemblies in HPRC release 2 and confirmed the correctness of three novel structural configurations.

bioRxiv (Cold Spring Harbor Laboratory)
Howard Hughes Medical Institute (US), University of California, Santa Cruz (US), University of Washington (US)
Life below water
Openalex Percentile: Top 37%
Genomics and Phylogenetic Studies
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Evaluating genome assemblies with HMM-Flagger — Taylor Real, Julian Lucas, et al. · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS