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CCMetagen:宏基因组数据中真核生物和原核生物的全面准确鉴定。

CCMetagen: comprehensive and accurate identification of eukaryotes and prokaryotes in metagenomic data.

机构信息

Marie Bashir Institute for Infectious Diseases and Biosecurity and Faculty of Medicine and Health, Sydney Medical School, Westmead Clinical School, The University of Sydney, Sydney, NSW, 2006, Australia.

Centre for Infectious Diseases and Microbiology, Westmead Institute for Medical Research, Westmead, NSW, 2145, Australia.

出版信息

Genome Biol. 2020 Apr 28;21(1):103. doi: 10.1186/s13059-020-02014-2.


DOI:10.1186/s13059-020-02014-2
PMID:32345331
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7189439/
Abstract

There is an increasing demand for accurate and fast metagenome classifiers that can not only identify bacteria, but all members of a microbial community. We used a recently developed concept in read mapping to develop a highly accurate metagenomic classification pipeline named CCMetagen. The pipeline substantially outperforms other commonly used software in identifying bacteria and fungi and can efficiently use the entire NCBI nucleotide collection as a reference to detect species with incomplete genome data from all biological kingdoms. CCMetagen is user-friendly, and the results can be easily integrated into microbial community analysis software for streamlined and automated microbiome studies.

摘要

人们对能够准确快速识别细菌以及微生物群落中所有成员的宏基因组分类器的需求日益增长。我们利用最近在读取映射方面开发的一个概念,开发了一个名为 CCMetagen 的高度准确的宏基因组分类管道。该管道在识别细菌和真菌方面的性能明显优于其他常用软件,并且可以有效地使用整个 NCBI 核苷酸集合作为参考,以检测来自所有生物界的具有不完全基因组数据的物种。CCMetagen 用户友好,其结果可以轻松集成到微生物群落分析软件中,以实现微生物组研究的简化和自动化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/ecd0e30ec648/13059_2020_2014_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/e6c0c28b9498/13059_2020_2014_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/1161ef4b2dca/13059_2020_2014_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/57bb27c19229/13059_2020_2014_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/c4812d14a5f4/13059_2020_2014_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/ecd0e30ec648/13059_2020_2014_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/e6c0c28b9498/13059_2020_2014_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/1161ef4b2dca/13059_2020_2014_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/57bb27c19229/13059_2020_2014_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/c4812d14a5f4/13059_2020_2014_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a92/7189439/ecd0e30ec648/13059_2020_2014_Fig5_HTML.jpg

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本文引用的文献

[1]
Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities - a proof of concept under laboratory conditions.

IMA Fungus. 2019-8-8

[2]
The use of taxon-specific reference databases compromises metagenomic classification.

BMC Genomics. 2020-2-27

[3]
Improved metagenomic analysis with Kraken 2.

Genome Biol. 2019-11-28

[4]
Meta-transcriptomics reveals a diverse antibiotic resistance gene pool in avian microbiomes.

BMC Biol. 2019-4-8

[5]
KrakenUniq: confident and fast metagenomics classification using unique k-mer counts.

Genome Biol. 2018-11-16

[6]
Mycobiome diversity: high-throughput sequencing and identification of fungi.

Nat Rev Microbiol. 2019-1

[7]
Virus-virus interactions and host ecology are associated with RNA virome structure in wild birds.

Mol Ecol. 2018-11-22

[8]
RefSeq database growth influences the accuracy of k-mer-based lowest common ancestor species identification.

Genome Biol. 2018-10-30

[9]
First evidence for the joint dispersal of mycorrhizal fungi and plant diaspores by birds.

New Phytol. 2019-1-23

[10]
Rapid and precise alignment of raw reads against redundant databases with KMA.

BMC Bioinformatics. 2018-8-29

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