Evaluating genome assemblies with HMM-Flagger

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Authors: Mobin Asri, Jordan M. Eizenga, Prajna Hebbar, Taylor D. Real, Julian Lucas, Hailey Loucks, Alessandro Calicchio, Mark E. Diekhans, Evan E Eichler, Sofie Salama, Karen H. Miga, Benedict Paten
Cited by: 4
References: 31

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.

Fields of Study & Subjects

Genomics and Phylogenetic Studies Genetic Associations and Epidemiology Genomic variations and chromosomal abnormalities

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
2 March 2026
Language
EN
Document type
Preprint