five

Hi-C deconvolution of a human gut microbiome yields high-quality draft genomes and reveals plasmid-genome interactions.

收藏
NIAID Data Ecosystem2026-03-10 收录
下载链接:
https://www.ncbi.nlm.nih.gov/bioproject/PRJNA413092
下载链接
链接失效反馈
官方服务:
资源简介:
The assembly of high-quality genomes from mixed microbial samples is a long-standing problem in genomics and metagenomics. Here, we describe the application of ProxiMetaTM, a Hi-C-based metagenomic deconvolution method, to deconvolve a human fecal sample. This method uses the intra-cellular proximity signal captured by Hi-C as a direct indicator of which sequences originated in the same cell, enabling culture-free de novo deconvolution of mixed genomes without any reliance on a priori information. We show that ProxiMeta provides incredibly high accuracy and sensitivity deconvolution, yielding 50 near-complete microbial genomes (many of which are novel) from a single fecal sample, and outperforms state-of-the-art contig binning approaches at high-quality genome reconstruction. ProxiMeta shows particularly good performance in constructing high-quality genomes for diverse but poorly-characterized members of the human gut, and offers additional information about microbial genome biology. We further use ProxiMeta to reconstruct genome plasmid content and gene sharing of plasmids – tasks that traditional binning methods often fail to accomplish. Our findings suggest that ProxiMeta-based deconvolution can be useful to a variety of applications in genomics and metagenomics.
创建时间:
2017-10-03
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作