SUMMARY: We propose a new algorithm, "interval hashing," which distinguishes identical k-mers arising from different repeat sequences, particularly in complex repeat arrays such as alpha satellite HORs. We implement this algorithm as a fork of minimap2, named mm2-ivh. In local assembly of alpha satellite HORs, mm2-ivh accurately reconstructs more haplotypes than assemblers using standard minimizers. AVAILABILITY AND IMPLEMENTATION: mm2-ivh is available under the MIT license at https://github.com/ocxtal/mm2-ivh and runs on common Unix-compatible systems.

BACKGROUND: Genome graph is an emerging approach for representing structural variants on genomes with branches. For example, representing structural variants of cancer genomes as a genome graph is more natural than representing such genomes as differences from the linear reference genome. While more and more structural variants are being identified by long-read sequencing, many of them are difficult to visualize using existing structural variants visualization tools. To this end, visualization method for large genome graphs such as human cancer genome graphs is demanded. RESULTS: We developed MOdular Multi-scale Integrated Genome graph browser, MoMI-G, a web-based genome graph browser that can visualize genome graphs with structural variants and supporting evidences such as read alignments, read depth, and annotations. This browser allows more intuitive recognition of large, nested, and potentially more complex structural variations. MoMI-G has view modules for different scales, which allow users to view the whole genome down to nucleotide-level alignments of long reads. Alignments spanning reference alleles and those spanning alternative alleles are shown in the same view. Users can customize the view, if they are not satisfied with the preset views. In addition, MoMI-G has Interval Card Deck, a feature for rapid manual inspection of hundreds of structural variants. Herein, we describe the utility of MoMI-G by using representative examples of large and nested structural variations found in two cell lines, LC-2/ad and CHM1. CONCLUSIONS: Users can inspect complex and large structural variations found by long-read analysis in large genomes such as human genomes more smoothly and more intuitively. In addition, users can easily filter out false positives by manually inspecting hundreds of identified structural variants with supporting long-read alignments and annotations in a short time. SOFTWARE AVAILABILITY: MoMI-G is freely available at https://github.com/MoMI-G/MoMI-G under the MIT license.

The burden of robot maintenance in the car industry (e.g. overhaul) is increasing drastically year after year. Although inspection and maintenance are indispensable in view of preventive maintenance, it is most important to accurately know the life expectancy of mechanical parts constituting a robot in order to execute the inspection and maintenance operations at the minimum investment. We therefore discuss the fact that the wear of gears is a dominant life expectancy factor of mechanical parts and we make observations on wear phenomenon in view of tribology. Based on the observations, we propose wear estimation models with improved lubrication and the improvement is applied to actual robots. In addition, we integrated the models with the robot off-line programming system and developed a CAE system capable of estimating the robot life expectancy at the time of preparation of robot teaching data.