De-biasing microbiome sequencing data: bacterial morphology-based correction of extraction bias and correlates of chimera formation

Abstract excerpt

INTRODUCTION: Microbiome amplicon sequencing data are distorted by multiple protocol-dependent biases from bacterial DNA extraction, contamination, sequence errors, and chimeras, hindering clinical microbiome applications. In particular, extraction bias is a major confounder in sequencing-based microbiome analyses, with no correction method available to date. Here, we suggest using mock community controls to...

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