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Table 1 Summary statistics for the different bioinformatic pipelines

From: A framework for assessing 16S rRNA marker-gene survey data analysis methods using mixtures.

Pipelines

Features

Sparsity

Total abundance

Drop-out rate

DADA2

3 144

0.93

68 649 (1661–112 058)

0.24 (0.18–0.59)

Mothur

3 8358

0.98

53 775 (1265–87 806)

0.40 (0.35–0.62)

QIIME

11 385

0.94

25 254 (517–46 897)

0.70 (0.62–0.97)

  1. DADA2 is a denoising sequence inference pipeline, QIIME is an open-reference clustering pipeline, and Mothur is a de novo clustering pipeline. NTC samples (no template controls) were excluded from summary statistics. Sparsity is the proportion of 0’s in the count table. Features is the total number of OTUs (QIIME and Mothur) or SVs (DADA2) in the count tables. Sample coverage is the median and range (minimum-maximum) per sample total abundance. Drop-out rate is the proportion of reads removed while processing the sequencing data for each bioinformatic pipeline