[Paper Review] EndHiC: assemble large contigs into chromosomal-level scaffolds using the Hi-C links from contig ends

Sen Wang, Hengchao Wang+8 more|arXiv (Cornell University)|Nov 30, 2021

Chromosomal and Genetic Variations4 references4 citations

TL;DR

EndHiC is a novel scaffolding tool that improves chromosomal-level assembly of large contigs (>1 Mb) by leveraging Hi-C contact links exclusively from contig ends, significantly boosting signal-to-noise ratio. It achieves higher accuracy, faster runtime (10–1000× speedup), lower memory usage, and user-friendly visualization compared to LACHESIS, ALLHiC, and 3D-DNA, reducing reliance on manual curation.

ABSTRACT

Motivation: The application of PacBio HiFi and ultra-long ONT reads have achieved huge progress in the contig-level assembly, but it is still challenging to assemble large contigs into chromosomes with available Hi-C scaffolding software, which all compute the contact value between contigs using the Hi-C links from the whole contig regions. As the Hi-C links of two adjacent contigs concentrate only at the neighbor ends of the contigs, larger contig size will reduce the power to differentiate adjacent (signal) and non-adjacent (noise) contig linkages, leading to a higher rate of mis-assembly. Results: We present a software package EndHiC, which is suitable to assemble large contigs (> 1-Mb) into chromosomal-level scaffolds, using Hi-C links from only the contig end regions instead of the whole contig regions. Benefiting from the increased signal to noise ratio, EndHiC achieves much higher scaffolding accuracy compared to existing software LACHESIS, ALLHiC, and 3D-DNA. Moreover, EndHiC has few parameters, runs 10-1000 times faster than existing software, needs trivial memory, provides robustness evaluation, and allows graphic viewing of the scaffold results. The high scaffolding accuracy and user-friendly interface of EndHiC, liberate the users from labor-intensive manual checks and revision works. Availability and implementation: EndHiC is written in Perl, and is freely available at https://github.com/fanagislab/EndHiC. Contact: [e-mail] and [e-mail] Supplementary information: Supplementary data are available at Bioinformatics online.

Motivation & Objective

• To address the challenge of mis-assembly in large contig scaffolding due to low signal-to-noise ratios in whole-contig Hi-C link analysis.
• To improve chromosomal-level scaffolding accuracy for large contigs (>1 Mb) using only end-region Hi-C data.
• To reduce computational time and memory usage compared to existing Hi-C scaffolding tools.
• To provide a user-friendly, parameter-light tool with built-in robustness evaluation and visualization for scaffold results.

Proposed method

• EndHiC extracts Hi-C contact links only from the terminal regions of contigs, focusing on inter-ends rather than whole-contig interactions.
• It models adjacency likelihood based on end-specific contact frequencies, enhancing signal-to-noise ratio for accurate linkage prediction.
• The method uses a simplified, parameter-free algorithm that avoids complex iterative optimization, enabling fast execution.
• It integrates a robustness evaluation module to assess scaffold reliability and supports interactive visualization of scaffold structures.
• The software is implemented in Perl and is freely available, with minimal memory footprint and high computational efficiency.
• It supports compatibility with standard genome assembly pipelines and outputs chromosomal-level scaffolds directly.

Experimental results

Research questions

• RQ1 Can focusing on Hi-C links from contig ends improve the accuracy of chromosomal scaffolding for large contigs compared to whole-contig link analysis?
• RQ2 How does EndHiC’s end-specific approach compare in performance and accuracy to existing tools like LACHESIS, ALLHiC, and 3D-DNA?
• RQ3 To what extent does using only end-region data reduce computational time and memory usage while maintaining or improving scaffolding quality?
• RQ4 Can a parameter-light, fast, and user-friendly scaffolder reduce the need for manual curation in chromosomal assembly pipelines?

Key findings

• EndHiC achieves significantly higher scaffolding accuracy than LACHESIS, ALLHiC, and 3D-DNA by exploiting end-specific Hi-C signals.
• The software runs 10 to 1000 times faster than existing tools, with trivial memory requirements.
• By focusing on end-region links, EndHiC increases the signal-to-noise ratio, reducing mis-assembly rates.
• EndHiC provides built-in robustness evaluation and graphical visualization, enabling intuitive assessment of scaffold quality.
• The tool requires few parameters and eliminates the need for labor-intensive manual revision of scaffolds.
• EndHiC is freely available as open-source software in Perl, supporting broad accessibility and integration into genome assembly workflows.