APSCALE: advanced pipeline for simple yet comprehensive analyses of DNA metabarcoding data

Author:

Buchner Dominik1,Macher Till-Hendrik1ORCID,Leese Florian12ORCID

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

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