henhao
Sign in
BioinformaticsbioRxiv
Preprint

MetaTrass: High-quality metagenome assembly on the human gut microbiome by co-barcoding sequencing reads

Yanwei QiiD, Shengqiang Gu, Yue ZhangiD, Lidong GuoiD, Mengyang XuiD, Xiaofang ChengiD, Ou WangiD, Jianwei CheniD, Xiaodong FangiD, Xin LiuiD, Li DengiD, Guangyi FaniD

PDFDOICode

Abstract

With the development of sequencing technologies and computational analysis in metagenomics, the genetic diversity of non-conserved regions has been receiving intensive attention to unravel the human gut microbial community. However, it remains a challenge to obtain enough microbial draft genomes at a high resolution from a single sample. In this work, we presented MetaTrass with a strategy of binning first and assembling later to assemble high-quality draft genomes based on metagenomics co-barcoding reads and the public reference genomes. We applied the tool to the single tube long fragment reads datasets for four human faecal samples, and generated more high-quality draft genomes with longer contiguity and higher resolution than the common combination strategies of genome assembling and binning. A total of 178 high-quality genomes was successfully assembled by MetaTrass, but the maximum of 58 was generated by the optimal common combination strategy in our tests. These high-quality genomes paved the way for genetic diversity and lineage analysis among different samples. With the high capability of assembling high-quality genomes of metagenomics datasets, MetaTrass will facilitate the study of spatial characters and dynamics of complex microbial communities at high resolution. The open-source code of MetaTrass is available at https://github.com/BGI-Qingdao/MetaTrass.

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISPortik '24Kim '22Vosloo '21Bertrand '18Bishara '18Cepeda '17
68% semantic matchMicrobiology
Daniel M. Portik, Xiaowen Feng, Gaëtan Benoit+17 more·bioRxiv·May 10, 2024· 25 citations