Tedersoo Leho, Ramirez Kelly S, Nilsson R Henrik, Kaljuvee Aivi, Kõljalg Urmas, Abarenkov Kessy
Natural History Museum, University of Tartu, 14a Ravila, 50411 Tartu, Estonia.
Netherlands Institute of Ecology, Droevendaalsesteeg 10, 6708 PB Wageningen, The Netherlands.
Gigascience. 2015 Jul 31;4:34. doi: 10.1186/s13742-015-0074-5. eCollection 2015.
High-throughput sequencing-based metabarcoding studies produce vast amounts of ecological data, but a lack of consensus on standardization of metadata and how to refer to the species recovered severely hampers reanalysis and comparisons among studies. Here we propose an automated workflow covering data submission, compression, storage and public access to allow easy data retrieval and inter-study communication. Such standardized and readily accessible datasets facilitate data management, taxonomic comparisons and compilation of global metastudies.
基于高通量测序的宏条形码研究产生了大量的生态数据,但在元数据标准化以及如何指代所鉴定出的物种方面缺乏共识,这严重阻碍了研究之间的重新分析和比较。在此,我们提出了一个自动化工作流程,涵盖数据提交、压缩、存储和公共访问,以便于数据检索和研究间的交流。这样标准化且易于获取的数据集有助于数据管理、分类比较以及全球元研究的编纂。