Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcodingShow others and affiliations
2018 (English)In: MycoKeys, ISSN 1314-4057, E-ISSN 1314-4049, no 39, p. 29-40Article in journal (Refereed) Published
Abstract [en]
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.
Place, publisher, year, edition, pages
PENSOFT PUBL , 2018. no 39, p. 29-40
Keywords [en]
Microbial communities, microbiome, mycobiome, fungal biodiversity, metagenomics, amplicon sequencing
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:uu:diva-364235DOI: 10.3897/mycokeys.39.28109ISI: 000444106400001PubMedID: 30271256OAI: oai:DiVA.org:uu-364235DiVA, id: diva2:1258738
2018-10-252018-10-252018-10-25Bibliographically approved