Puzzle Hi-C: an accurate scaffolding software
Lin, G.; Huang, Z.; Yue, T.; Chai, J.; Li, Y.; Yang, H.; Qin, W.; Yang, G.; Murphy, R. W.; Zhang, Y.-p.; Zhang, Z.; Zhou, W.; Luo, J.
Show abstract
High-quality, chromosome-scale genomes are essential for genomic analyses. Analyses, including 3D genomics, epigenetics, and comparative genomics rely on a high-quality genome assembly, which is often accomplished with the assistance of Hi-C data. Current Hi-C-assisted assembling algorithms either generate ordering and orientation errors or fail to assemble high-quality chromosome-level scaffolds. Here, we offer the software Puzzle Hi-C, which uses Hi-C reads to accurately assign contigs or scaffolds to chromosomes. Puzzle Hi-C uses the triangle region instead of the square region to count interactions in a Hi-C heatmap. This strategy dramatically diminishes scaffolding interference caused by long-range interactions. This software also introduces a dynamic, triangle window strategy during assembly. Initially small, the window expands with interactions to produce more effective clustering. Puzzle Hi-C outperforms available scaffolding tools.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- A comprehensive benchmark of graph-based genetic variant genotyping algorithms on plant genomes for creating an accurate ensemble pipeline 95%
- MetaBinner: a high-performance and stand-alone ensemble binning method to recover individual genomes from complex microbial communities 94%
- High-Quality Genomes of Nanopore Sequencing by Homologous Polishing 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.