Data from: Sequence clustering threshold has little effect on the recovery of microbial community structure

Analysis of microbial community structure by multivariate ordination methods, using data obtained by high throughput sequencing of amplified markers (i.e., DNA metabarcoding), often requires clustering of DNA sequences into operational taxonomic units (OTUs). Parameters for the clustering procedure...

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Bibliographic Details
Main Authors: Botnen, Synnøve Smebye, Davey, Marie L., Halvorsen, Rune, Kauserud, Håvard, Davey, Marie Louise
Format: Dataset
Language:unknown
Published: Data Archiving and Networked Services (DANS) 2018
Subjects:
geo
Online Access:https://doi.org/10.5061/dryad.jb79430
Description
Summary:Analysis of microbial community structure by multivariate ordination methods, using data obtained by high throughput sequencing of amplified markers (i.e., DNA metabarcoding), often requires clustering of DNA sequences into operational taxonomic units (OTUs). Parameters for the clustering procedure tend not to be justified but are set by tradition rather than being based on explicit knowledge. In this study, we explore the extent to which ordination results are affected by variation in parameter settings for the clustering procedure. Amplicon sequence data from nine microbial community studies, representing different sampling designs, spatial scales and ecosystems, were subjected to clustering into OTUs at seven different similarity thresholds (clustering thresholds) ranging from 87% to 99% sequence similarity. The 63 data sets thus obtained were subjected to parallel DCA and GNMDS ordinations. The resulting community structures were highly similar across all clustering thresholds. We explain this pattern by the existence of strong ecological structuring gradients and phylogenetically diverse sets of abundant OTUs that are highly stable across clustering thresholds. Removing low abundance, rare OTUs had negligible effects on community patterns. Our results indicate that microbial data sets with a clear gradient structure are highly robust to choice of sequence clustering threshold. Dataset4_RawDataTarball containing raw data in the form of 5 .sff.txt files. Corresponding mapping files for demultiplexing of each raw file are provided, in addition to a combined mapping file with treatment information.Dataset4_Dryad.tar.gzDataset7_DryadTar archive containing raw data for Dataset 7 in the form of 4 .sff files. Corresponding mapping files for demultiplexing are provided for each data file.Dataset3_DryadTar archive consisting of 20 .fastq files representing raw, demultiplexed data.Dataset9_DryadTar archive containing 20 .fastq files representing raw, demultiplexed illumina sequencing ...