Integrating Hi-C links with assembly graphs for chromosome-scale assembly

作者：Jay Ghurye, A. Rhie, B. Walenz, A. Schmitt, Siddarth Selvaraj, Mihai Pop, A. Phillippy, S. Koren · 发表于：bioRxiv · 年份：2018 · DOI：10.1371/journal.pcbi.1007273 · 被引用次数：646 · 研究领域：Computer Science、Medicine、Biology

Motivation Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. Results We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. Availability and Implementation The Python and C++ code for our method is openly available at https://github.com/machinegun/SALSA Contact sergey.koren@nih.gov, adam.phillippy@nih.gov Supplementary information Not available online.