Phytool, a ShinyApp to homogenise taxonomy of freshwater microalgae from DNA barcodes and microscopic observations

Alexis Canino, A. Bouchez, C. Laplace-Treyture, I. Domaizon, F. Rimet
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引用次数: 3

Abstract

Methods for biomonitoring of freshwater phytoplankton are evolving rapidly with eDNA-based methods, offering great complementarity with microscopy. Metabarcoding approaches have been more commonly used over the last years, with a continuous increase in the amount of data generated. Depending on the researchers and the way they assigned barcodes to species (bioinformatic pipelines and molecular reference databases), the taxonomic assignment obtained for HTS DNA reads might vary. This is also true for traditional taxonomic studies by microscopy with regular adjustments of the classification and taxonomy. For those reasons (leading to non-homogeneous taxonomies), gap-analyses and comparisons between studies become even more challenging and the curation processes to find potential consensus names are time-consuming. Here, we present a web-based application (Phytool), developed with ShinyApp (Rstudio), that aims to make the harmonisation of taxonomy easier and in a more efficient way, using a complete and up-to-date taxonomy reference database for freshwater microalgae. Phytool allows users to homogenise and update freshwater phytoplankton taxonomical names from sequence files and data tables directly uploaded in the application. It also gathers barcodes from curated references in a user-friendly way in which it is possible to search for specific organisms. All the data provided are downloadable with the possibility to apply filters in order to select only the required taxa and fields (e.g. specific taxonomic ranks). The main goal is to make accessible to a broad range of users the connection between microscopy and molecular biology and taxonomy through different ready-to-use functions. This study estimates that only 25% of species of freshwater phytoplankton in Phytobs are associated with a barcode. We plead for an increased effort to enrich reference databases by coupling taxonomy and molecular methods. Phytool should make this crucial work more efficient. The application is available at https://caninuzzo.shinyapps.io/phytool_v1/
Phytol,一种从DNA条形码和显微镜观察中均匀化淡水微藻分类的新应用
基于eDNA的淡水浮游植物生物监测方法正在迅速发展,与显微镜技术有很大的互补性。随着生成的数据量的不断增加,元代码方法在过去几年中越来越常用。根据研究人员以及他们为物种分配条形码的方式(生物信息学管道和分子参考数据库),HTS DNA读数的分类分配可能会有所不同。通过显微镜对分类和分类学进行定期调整的传统分类学研究也是如此。由于这些原因(导致分类法不同质),研究之间的差距分析和比较变得更加具有挑战性,寻找潜在一致名称的管理过程非常耗时。在这里,我们介绍了一个基于网络的应用程序(Phytol),该应用程序是由ShinyApp(Rstudio)开发的,旨在使用一个完整且最新的淡水微藻分类学参考数据库,使分类学的协调更容易、更高效。Phytol允许用户从直接上传到应用程序中的序列文件和数据表中同质化和更新淡水浮游植物分类名称。它还以用户友好的方式从精心策划的参考文献中收集条形码,从而可以搜索特定的生物体。提供的所有数据都可以下载,可以应用过滤器,以便只选择所需的分类群和字段(例如特定的分类等级)。主要目标是通过不同的现成功能,让广大用户能够访问显微镜与分子生物学和分类学之间的联系。这项研究估计,Phytobs中只有25%的淡水浮游植物与条形码有关。我们呼吁通过结合分类学和分子方法来丰富参考数据库。Phytol应该使这项至关重要的工作更有效率。该应用程序可在https://caninuzzo.shinyapps.io/phytool_v1/
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Metabarcoding and Metagenomics
Metabarcoding and Metagenomics Agricultural and Biological Sciences-Animal Science and Zoology
CiteScore
5.40
自引率
0.00%
发文量
25
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