Critical Assessment of Metagenome Interpretation-a benchmark of metagenomics software.
Critical Assessment of Metagenome Interpretation-a benchmark of metagenomics software.
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DOI：
10.1038/nmeth.4458
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发表时间：
2017-11
期刊：
影响因子：
48
通讯作者：
McHardy AC
中科院分区：
文献类型：
--
作者：
Sczyrba A;Hofmann P;Belmann P;Koslicki D;Janssen S;Dröge J;Gregor I;Majda S;Fiedler J;Dahms E;Bremges A;Fritz A;Garrido-Oter R;Jørgensen TS;Shapiro N;Blood PD;Gurevich A;Bai Y;Turaev D;DeMaere MZ;Chikhi R;Nagarajan N;Quince C;Meyer F;Balvočiūtė M;Hansen LH;Sørensen SJ;Chia BKH;Denis B;Froula JL;Wang Z;Egan R;Don Kang D;Cook JJ;Deltel C;Beckstette M;Lemaitre C;Peterlongo P;Rizk G;Lavenier D;Wu YW;Singer SW;Jain C;Strous M;Klingenberg H;Meinicke P;Barton MD;Lingner T;Lin HH;Liao YC;Silva GGZ;Cuevas DA;Edwards RA;Saha S;Piro VC;Renard BY;Pop M;Klenk HP;Göker M;Kyrpides NC;Woyke T;Vorholt JA;Schulze-Lefert P;Rubin EM;Darling AE;Rattei T;McHardy AC
在宏基因组分析中，用于组装、分类特征分析和分箱的计算方法是促进下游生物数据解释的关键组成部分。然而，由于缺乏对基准数据集和评估指标的共识，使适当的绩效评估变得复杂。宏基因组解释的关键评估（CAMI）挑战已经吸引了全球开发者社区，以前所未有的复杂性和现实性的数据集为基准。基准宏基因组是从约700种新测序的微生物和约600种新型病毒和质粒中产生的，包括彼此之间以及与公开可用的基因组具有不同程度的相关性的基因组，并代表常见的实验设置。在所有数据集中，组装和基因组分箱程序对于由单个基因组代表的物种表现良好，而性能受到相关菌株的存在的实质性影响。分类剖析和装箱程序精通高分类等级，与一个显着的性能下降低于家庭水平。参数设置大大影响性能，强调程序再现性的重要性。在强调计算宏基因组学当前面临的挑战的同时，CAMI的结果为软件选择提供了路线图，以回答特定的研究问题。
In metagenome analysis, computational methods for assembly, taxonomic profiling and binning are key components facilitating downstream biological data interpretation. However, a lack of consensus about benchmarking datasets and evaluation metrics complicates proper performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on datasets of unprecedented complexity and realism. Benchmark metagenomes were generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids, including genomes with varying degrees of relatedness to each other and to publicly available ones and representing common experimental setups. Across all datasets, assembly and genome binning programs performed well for species represented by individual genomes, while performance was substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below the family level. Parameter settings substantially impacted performances, underscoring the importance of program reproducibility. While highlighting current challenges in computational metagenomics, the CAMI results provide a roadmap for software selection to answer specific research questions.
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影响因子：
2.7
作者：
Gregor I;Dröge J;Schirmer M;Quince C;McHardy AC
通讯作者：
McHardy AC
影响因子：
3.7
作者：
Chapman JA;Ho I;Sunkara S;Luo S;Schroth GP;Rokhsar DS
通讯作者：
Rokhsar DS
影响因子：
64.8
作者：
Arumugam, Manimozhiyan;Raes, Jeroen;Pelletier, Eric;Le Paslier, Denis;Yamada, Takuji;Mende, Daniel R.;Fernandes, Gabriel R.;Tap, Julien;Bruls, Thomas;Batto, Jean-Michel;Bertalan, Marcelo;Borruel, Natalia;Casellas, Francesc;Fernandez, Leyden;Gautier, Laurent;Hansen, Torben;Hattori, Masahira;Hayashi, Tetsuya;Kleerebezem, Michiel;Kurokawa, Ken;Leclerc, Marion;Levenez, Florence;Manichanh, Chaysavanh;Nielsen, H. Bjorn;Nielsen, Trine;Pons, Nicolas;Poulain, Julie;Qin, Junjie;Sicheritz-Ponten, Thomas;Tims, Sebastian;Torrents, David;Ugarte, Edgardo;Zoetendal, Erwin G.;Wang, Jun;Guarner, Francisco;Pedersen, Oluf;de Vos, Willem M.;Brunak, Soren;Dore, Joel;Weissenbach, Jean;Ehrlich, S. Dusko;Bork, Peer
通讯作者：
Bork, Peer
DOI：
10.1073/pnas.0409727102
发表时间：
2005-02-15
影响因子：
11.1
作者：
Konstantinidis, KT;Tiedje, JM
通讯作者：
Tiedje, JM
影响因子：
2.7
作者：
Kang DD;Froula J;Egan R;Wang Z
通讯作者：
Wang Z