Affiliation:
1. University of Duisburg-Essen, Faculty of Biology, Aquatic Ecosystem Research , Essen 45141, Germany
2. Univeresity of Duisburg-Essen, Centre for Water and Environmental Research (ZWU) , Essen 45141, Germany
Abstract
Abstract
Summary
DNA metabarcoding is an emerging approach to assess and monitor biodiversity worldwide and consequently the number and size of data sets increases exponentially. To date, no published DNA metabarcoding data processing pipeline exists that is (i) platform independent, (ii) easy to use [incl. graphical user interface (GUI)], (iii) fast (does scale well with dataset size) and (iv) complies with data protection regulations of e.g. environmental agencies. The presented pipeline APSCALE meets these requirements and handles the most common tasks of sequence data processing, such as paired-end merging, primer trimming, quality filtering, clustering and denoising of any popular metabarcoding marker, such as internal transcribed spacer, 16S or cytochrome c oxidase subunit I. APSCALE comes in a command line and a GUI version. The latter provides the user with additional summary statistics options and links to GUI-based downstream applications.
Availability and implementation
APSCALE is written in Python, a platform-independent language, and integrates functions of the open-source tools, VSEARCH (Rognes et al., 2016), cutadapt (Martin, 2011) and LULU (Frøslev et al., 2017). All modules support multithreading to allow fast processing of larger DNA metabarcoding datasets. Further information and troubleshooting are provided on the respective GitHub pages for the command-line version (https://github.com/DominikBuchner/apscale) and the GUI-based version (https://github.com/TillMacher/apscale_gui), including a detailed tutorial.
Supplementary information
Supplementary data are available at Bioinformatics online.
Funder
GeDNA project, funded by the German Federal Environment Agency
Deutsche Forschungsgemeinschaft
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
Cited by
22 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献