Contamination issues

First published: July 2016. Updated: April 2018


KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples
Jeremiah J. Minich – mSystems – March 2018

Systematic Bias Introduced by Genomic DNA Template Dilution in 16S rRNA Gene-Targeted Microbiota Profiling in Human Stool Homogenates – Francesco Multinu – mSphere – March 2018

Microbial Lineages in Sarcoidosis. A Metagenomic Analysis Tailored for Low–Microbial Content Samples – Erik L. Clarke – American Journal of Respiratory and Critical Care Medicine – January 2018

Decontaminating eukaryotic genome assemblies with machine learning– Janna L. Fierst – BMC Bioinformatics – December 2017

Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data – Nicole M Davis – bioRxiv – November 2017

Impact of DNA extraction, sample dilution, and reagent contamination on 16S rRNA gene sequencing of human feces – Eliana P. Velásquez-Mejía – Applied Microbiology and Biotechnology – October 2017

Inherent bacterial DNA contamination of extraction and sequencing reagents may affect interpretation of microbiota in low bacterial biomass samples – Angela Glassing – Gut Pathogens – May 2016

Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR – Vladimir Lazarevic – BMC Microbiology – April 2016

Deriving accurate microbiota profiles from human samples with low bacterial content through post-sequencing processing of Illumina MiSeq data – Jake Jervis-Bardy  – BMC Microbiome – May 2015

Tracking down the sources of experimental contamination in microbiome studies – Sophie Weiss – Genome Biology – December 2014

Contamination plagues some microbiome studies – Elizabeth Pennisi – Science – November 2014

Reagent and laboratory contamination can critically impact sequence-based microbiome analyses – Susannah J Salter – BMC Biology – November 2014