phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.
phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.
复制标题
DOI：
10.1371/journal.pone.0061217
复制
发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Holmes S
中科院分区：
文献类型：
--
作者：
McMurdie PJ;Holmes S
通过DNA测序分析微生物群落带来了许多挑战：将不同类型的数据与生态学，遗传学，遗传学，多元统计，可视化和测试方法相结合。随着现在追求的实验设计的广度增加，通常需要特定于项目的统计分析，而这些分析通常很难（或不可能）让同行研究人员独立重现。绝大多数可重复执行这些分析的必要工具已经在R及其扩展（包）中实现，但对高通量微生物组普查数据的支持有限。在这里，我们描述了一个软件项目，RISseq，致力于面向对象的表示和分析的微生物普查数据在R。它支持从各种常见格式导入数据，以及许多分析技术。这些包括校准、过滤、子集化、聚集、多表比较、多样性分析、并行化Fast UniFrac、排序方法和出版质量图形的制作;所有这些都以易于记录、共享和修改的方式进行。我们将展示如何将其他R包中的函数应用于以JavaScript表示的数据，说明大量开源分析技术的可用性。我们讨论了使用可重复的研究工具，这在其他领域很常见，但在高度并行的微生物普查数据分析中仍然很少见。我们已经提供了所有必要的材料，以完全复制本文中包含的分析和数字，这是可复制研究的最佳实践的一个例子。R语言的Apriseq项目是一个新的开源软件包，可以从GitHub和Bioconductor网站上免费获得。
The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
登录
查看更多内容
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
影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J
影响因子：
56.9
作者：
FLEISCHMANN, RD;ADAMS, MD;VENTER, JC
通讯作者：
VENTER, JC
CLOVR：使用云计算从桌面上自动化和便携式序列分析的虚拟机。
影响因子：
3
作者：
Angiuoli SV;Matalka M;Gussman A;Galens K;Vangala M;Riley DR;Arze C;White JR;White O;Fricke WF
通讯作者：
Fricke WF
影响因子：
14.9
作者：
Cole JR;Wang Q;Cardenas E;Fish J;Chai B;Farris RJ;Kulam-Syed-Mohideen AS;McGarrell DM;Marsh T;Garrity GM;Tiedje JM
通讯作者：
Tiedje JM