ArticleBriefings in bioinformatics2024
DEGAP: Dynamic elongation of a genome assembly path.
Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Automatic generation of model sequences for complex regions in assembly graphs with TTT.Cell genomics · 2026Article
- Automatic Generation of Model Sequences for Complex Regions in Assembly Graphs.bioRxiv : the preprint server for biology · 2026Article
- RAGA: a reference-assisted genome assembly tool for efficient population-scale assembly.Horticulture research · 2025Article
- Gap-free genome assemblies of two Pyrus bretschneideri cultivars and GWAS analyses identify a CCCH zinc finger protein as a key regulator of stone cell formation in pear fruit.Plant communications · 2025Article
- Near telomere-to-telomere genome assemblies of Silkie Gallus gallus and Mallard Anas platyrhynchos restored the structure of chromosomes and "missing" genes in birds.Journal of animal science and biotechnology · 2025Article
- A complete reference genome for the soybean cv. Jack.Plant communications · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
Genome assembly remains to be a major task in genomic research. Despite the development over the past decades of different assembly software programs and algorithms, it is still a great challenge to assemble a complete genome without any gaps. With the latest DNA circular consensus sequencing (CCS) technology, several assembly programs can now build a genome from raw sequencing data to contigs; however, some complex sequence regions remain as unresolved gaps. Here, we present a novel gap-filling software, DEGAP (Dynamic Elongation of a Genome Assembly Path), that resolves gap regions by utilizing the dual advantages of accuracy and length of high-fidelity (HiFi) reads. DEGAP identifies differences between reads and provides 'GapFiller' or 'CtgLinker' modes to eliminate or shorten gaps in genomes. DEGAP adopts an iterative elongation strategy that automatically and dynamically adjusts parameters according to three complexity factors affecting the genome to determine the optimal extension path. DEGAP has already been successfully applied to decipher complex genomic regions in several projects and may be widely employed to generate more gap-free genomes.
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Registered trials
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