Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding

0498742 - MBÚ 2019 RIV BG eng J - Článek v odborném periodiku
Aslan, S. - Nilsson, R.H. - Wurzbacher, Ch. - Baldrian, Petr - Tedersoo, L. - Bahram, M.
Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding.
MycoKeys. Roč. 39, SEP 10 (2018), s. 29-40. ISSN 1314-4057. E-ISSN 1314-4049
Institucionální podpora: RVO:61388971
Klíčová slova: Microbial communities * microbiome * fungal biodiversity
Obor OECD: Microbiology
Impakt faktor: 2.435, rok: 2018

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.
Trvalý link: http://hdl.handle.net/11104/0291010