2018
DOI: 10.12688/f1000research.9227.2
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NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes

Abstract: Background: Massive high-throughput sequencing of short, hypervariable segments of the 16S ribosomal RNA (rRNA) gene has transformed the methodological landscape describing microbial diversity within and across complex biomes. However, several studies have shown that the methodology rather than the biological variation is responsible for the observed sample composition and distribution. This compromises meta-analyses, although this fact is often disregarded. Results: To facilitate true meta-analysis of microbi… Show more

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Cited by 130 publications
(148 citation statements)
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“…OTU-classification was performed using the NG-Tax pipeline (30). A large portion (7-55%) of OTUs could not be classified even at phylum level (Figure 3a).…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…OTU-classification was performed using the NG-Tax pipeline (30). A large portion (7-55%) of OTUs could not be classified even at phylum level (Figure 3a).…”
Section: Resultsmentioning
confidence: 99%
“…Sequence analysis of the raw data was performed in NG-Tax using default settings (30). In short: paired-end libraries were demultiplexed using read pairs with perfectly matching barcodes.…”
Section: Methodsmentioning
confidence: 99%
“…A 2-step PCR strategy was applied to generate barcoded amplicons from the V1—V2 region of bacterial 16S rRNA genes as described previously [36]. Sequence analysis was performed using NG-Tax [37]. Operational taxonomic units (OTUs) were assigned taxonomy using uclust [38] in an open reference approach against the SILVA 16S rRNA gene reference database (LTPs128_SSU) [39].…”
Section: Methodsmentioning
confidence: 99%
“…', a biomolecular analysis of microbial community composition was performed. PCR-amplified fragments of microbial 16S ribosomal RNA (rRNA) genes of all three samples were analysed using MiSeq Illumina sequencing to explore the archaeal and bacterial content of the samples (Ramiro-Garcia et al, 2016). Similarity of the observed microbial communities was plotted using principal component analysis (PCA) (Fig.…”
Section: Resultsmentioning
confidence: 99%