LoMA -Long-read localized assembly- project. Homo sapiens

Long-read sequencing data has a high error rate, and its handling has not been established. Therefore, it is important to establish useful bioinformatics analysis methods. Mapping-based analysis and whole-genome-assembly-based variant detection have problems such as errors due to repetitive sequences and lack of nucleotide sequence information. In this project, we develop a novel bioinformatics analysis method for long reads and applied it to whole genome analysis of two samples to elucidate the entire human insertion sequence and insertion mechanism.The Data Access Committee of the National Bioscience Database Center (NBDC) approved that this personal data was made published according to the NBDC Guidelines for Human Data Sharing (https://humandbs.biosciencedbc.jp/en/guidelines/data-sharing-guidelines) as the NBDC Research ID hum0386 and the application ID J-DS000829-001.