Along with recent developments in high-throughput sequencing (HTS) technologies and thus fast accumulation of HTS data, there has been a growing need and interest for developing tools for HTS data processing and communication. In particular, a number of bioinformatics tools have been designed for analysing metabarcoding data, each with specific features, assumptions and outputs. To evaluate the potential effect of the application of different bioinformatics workflow on the results, we compared the performance of different analysis platforms on two contrasting high-throughput sequencing data sets. Our analysis revealed that the computation time, quality of error filtering and hence output of specific bioinformatics process largely depends on the platform used. Our results show that none of the bioinformatics workflows appears to perfectly filter out the accumulated errors and generate Operational Taxonomic Units, although PipeCraft, LotuS and PIPITS perform better than QIIME2 and Galaxy for the tested fungal amplicon dataset. We conclude that the output of each platform requires manual validation of the OTUs by examining the taxonomy assignment values.

Braunschweig University of Technology Zoological Institute Mendelssohnstr 4 38106 Braunschweig Germany

Department of Ecology Swedish University of Agricultural Sciences Ulls väg 16 756 51 Uppsala Sweden

Department of Organismal Biology Evolutionary Biology Centre Uppsala University Norbyvägen 18D Uppsala Sweden

Gothenburg Global Biodiversity Centre Department of Biological and Environmental Sciences University of Gothenburg Box 461 405 30 Gothenburg Sweden

Institute of Ecology and Earth Science Tartu University 14a Ravila 50411 Tartu Estonia

Institute of Microbiology of the Czech Academy of Sciences Videnska 1083 14220 Praha 4 Czech Republic

Natural History Museum of Tartu University 14a Ravila 50411 Tartu Estonia

Technical University of Munich Am Coulombwall 3 85748 Garching Germany

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