Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data.

ABSTRACT:

Background

The accuracy of microbial community surveys based on marker-gene and metagenomic sequencing (MGS) suffers from the presence of contaminants-DNA sequences not truly present in the sample. Contaminants come from various sources, including reagents. Appropriate laboratory practices can reduce contamination, but do not eliminate it. Here we introduce decontam ( https://github.com/benjjneb/decontam ), an open-source R package that implements a statistical classification procedure that identifies contaminants in MGS data based on two widely reproduced patterns: contaminants appear at higher frequencies in low-concentration samples and are often found in negative controls.

Results

Decontam classified amplicon sequence variants (ASVs) in a human oral dataset consistently

SUBMITTER: Davis NM 

PROVIDER: S-EPMC6298009 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature