metasort

Most current approaches analyze metagenomic data with the participation of reference genomes. However, novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities still remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations on simulated dataset, salivary and gut microbiomes, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly.

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