Hybrid-denovo: A de novo OTU-picking pipeline integrating single-end and paired-end 16S sequence tags

Xianfeng Chen, Stephen Johnson, Patricio Jeraldo, Junwen Wang, Nicholas Chia, Jean Pierre A. Kocher, Jun Chen

Research output: Contribution to journalComment/debate

17 Scopus citations

Abstract

Background: Illumina paired-end sequencing has been increasingly popular for 16S rRNA gene-based microbiota profiling. It provides higher phylogenetic resolution than single-end reads due to a longer read length. However, the reverse read (R2) often has significant low base quality, and a large proportion of R2s will be discarded after quality control, resulting in a mixture of paired-end and single-end reads. A typical 16S analysis pipeline usually processes either paired-end or single-end reads but not a mixture. Thus, the quantification accuracy and statistical power will be reduced due to the loss of a large amount of reads. As a result, rare taxa may not be detectable with the paired-end approach, or low taxonomic resolution will result in a single-end approach. Results: To have both the higher phylogenetic resolution provided by paired-end reads and the higher sequence coverage by single-end reads, we propose a novel OTU-picking pipeline, hybrid-denovo, that can process a hybrid of single-end and paired-end reads. Using high-quality paired-end reads as a gold standard, we show that hybrid-denovo achieved the highest correlation with the gold standard and performed better than the approaches based on paired-end or single-end reads in terms of quantifying the microbial diversity and taxonomic abundances. By applying our method to a rheumatoid arthritis (RA) data set, we demonstrated that hybrid-denovo captured more microbial diversity and identified more RA-associated taxa than a paired-end or single-end approach. Conclusions: Hybrid-denovo utilizes both paired-end and single-end 16S sequencing reads and is recommended for 16S rRNA gene targeted paired-end sequencing data.

Original languageEnglish (US)
Pages (from-to)1-7
Number of pages7
JournalGigaScience
Volume7
Issue number3
DOIs
StatePublished - Mar 1 2018

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Keywords

  • 16S rRNA
  • Microbiome
  • OTU picking

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications

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