A RESTful API for accessing microbial community data for MG-RAST.
A RESTful API for accessing microbial community data for MG-RAST.
复制标题
DOI：
10.1371/journal.pcbi.1004008
复制
发表时间：
2015-01
影响因子：
4.3
通讯作者：
Meyer F
中科院分区：
文献类型：
--
作者：
Wilke A;Bischof J;Harrison T;Brettin T;D'Souza M;Gerlach W;Matthews H;Paczian T;Wilkening J;Glass EM;Desai N;Meyer F
近年来，宏基因组测序产生了大量的数据。例如，截至2013年夏季，MG-RAST已用于注释超过11万个数据集，总计超过43个太数据库。随着宏基因组测序在科学界的广泛应用，MG-RAST现有的基于网络的分析工具和基础设施提供了有限的数据检索和分析能力，例如多个数据集之间的比较分析。此外，虽然系统提供了许多分析工具，但并不全面。通过web服务API（应用程序编程接口）开放MG-RAST，我们极大地扩展了对MG-RAST数据的访问，并提供了一种使用第三方分析工具处理MG-RAST数据的机制。这个RESTful API使MG-RAST管道创建的所有数据和数据对象都可以作为JSON对象访问。作为美国能源部系统生物学知识库项目（KBase, http://kbase.us）的一部分，我们已经为MG-RAST实现了一个web服务API。该API补充了现有的MG-RAST web界面，并构成了KBase微生物群落功能的基础。此外，API向程序员公开了一个全面的数据集合。这个API使用RESTful （Representational State Transfer）实现，与大多数编程环境兼容，对于最终用户和第三方来说应该很容易使用。它提供了对序列数据、质量控制结果、注释和许多其他数据类型的全面访问。在可行的情况下，我们使用标准来公开数据和元数据。提供了多种语言的代码示例，既展示了API的多功能性，又为用户提供了一个起点。我们提供了一个API，它将MG-RAST中的数据公开给用户使用，从而极大地增强了MG-RAST服务的实用性。近年来，宏基因组测序产生了大量的数据。例如，截至2013年夏季，MG-RAST宏基因组学分析系统已用于注释超过11万个数据集，总计超过43个太数据库。随着宏基因组测序在科学界得到更广泛的应用，MG-RAST现有的基于网络的分析工具和基础设施提供了有限的比较分析能力（即数据集的数量）。此外，虽然系统提供了许多分析工具，但并不全面。通过web服务API（应用程序编程接口）开放MG-RAST，我们为其他人提供了一种编程方式，可以使用他们的生物信息学工具来处理MG-RAST数据。
Metagenomic sequencing has produced significant amounts of data in recent years. For example, as of summer 2013, MG-RAST has been used to annotate over 110,000 data sets totaling over 43 Terabases. With metagenomic sequencing finding even wider adoption in the scientific community, the existing web-based analysis tools and infrastructure in MG-RAST provide limited capability for data retrieval and analysis, such as comparative analysis between multiple data sets. Moreover, although the system provides many analysis tools, it is not comprehensive. By opening MG-RAST up via a web services API (application programmers interface) we have greatly expanded access to MG-RAST data, as well as provided a mechanism for the use of third-party analysis tools with MG-RAST data. This RESTful API makes all data and data objects created by the MG-RAST pipeline accessible as JSON objects. As part of the DOE Systems Biology Knowledgebase project (KBase, http://kbase.us) we have implemented a web services API for MG-RAST. This API complements the existing MG-RAST web interface and constitutes the basis of KBase's microbial community capabilities. In addition, the API exposes a comprehensive collection of data to programmers. This API, which uses a RESTful (Representational State Transfer) implementation, is compatible with most programming environments and should be easy to use for end users and third parties. It provides comprehensive access to sequence data, quality control results, annotations, and many other data types. Where feasible, we have used standards to expose data and metadata. Code examples are provided in a number of languages both to show the versatility of the API and to provide a starting point for users. We present an API that exposes the data in MG-RAST for consumption by our users, greatly enhancing the utility of the MG-RAST service. Metagenomic sequencing has produced significant amounts of data in recent years. For example, as of summer 2013, the MG-RAST metagenomics analysis system has been used to annotate over 110,000 data sets totaling over 43 Terabases. With metagenomic sequencing finding even wider adoption in the scientific community, the existing web-based analysis tools and infrastructure in MG-RAST provide limited capability for comparative analysis (i.e., number of data sets). Moreover, although the system provides many analysis tools, it is not comprehensive. By opening MG-RAST up via a web services API (application programmers interface) we have enabled a programmatic way for others to use their bioinformatics tools with MG-RAST data.
登录
查看更多内容
影响因子：
14.9
作者：
Hunter S;Jones P;Mitchell A;Apweiler R;Attwood TK;Bateman A;Bernard T;Binns D;Bork P;Burge S;de Castro E;Coggill P;Corbett M;Das U;Daugherty L;Duquenne L;Finn RD;Fraser M;Gough J;Haft D;Hulo N;Kahn D;Kelly E;Letunic I;Lonsdale D;Lopez R;Madera M;Maslen J;McAnulla C;McDowall J;McMenamin C;Mi H;Mutowo-Muellenet P;Mulder N;Natale D;Orengo C;Pesseat S;Punta M;Quinn AF;Rivoire C;Sangrador-Vegas A;Selengut JD;Sigrist CJ;Scheremetjew M;Tate J;Thimmajanarthanan M;Thomas PD;Wu CH;Yeats C;Yong SY
通讯作者：
Yong SY
影响因子：
9.2
作者：
McDonald D;Clemente JC;Kuczynski J;Rideout JR;Stombaugh J;Wendel D;Wilke A;Huse S;Hufnagle J;Meyer F;Knight R;Caporaso JG
通讯作者：
Caporaso JG
影响因子：
--
作者：
Coggill, Penny;Finn, Robert D;Bateman, Alex
通讯作者：
Bateman, Alex
影响因子：
3
作者：
Meyer, F.;Paarmann, D.;Edwards, R. A.
通讯作者：
Edwards, R. A.
影响因子：
14.9
作者：
Afrasiabi, Cyrus;Samad, Bushra;Sjoelander, Kimmen
通讯作者：
Sjoelander, Kimmen