AmpliCI: a high-resolution model-based approach for denoising Illumina amplicon data.

ABSTRACT:

Motivation

Next-generation amplicon sequencing is a powerful tool for investigating microbial communities. A main challenge is to distinguish true biological variants from errors caused by amplification and sequencing. In traditional analyses, such errors are eliminated by clustering reads within a sequence similarity threshold, usually 97%, and constructing operational taxonomic units, but the arbitrary threshold leads to low resolution and high false-positive rates. Recently developed 'denoising' methods have proven able to resolve single-nucleotide amplicon variants, but they still miss low-frequency sequences, especially those near more frequent sequences, because they ignore the sequencing quality information.

Results

We introduce AmpliCI, a reference-free, model-based

SUBMITTER: Peng X 

PROVIDER: S-EPMC7850112 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature