Abstract
Next-generation amplicon sequencing is widely used for surveying biological diversity in applications such as microbial metagenomics, immune system repertoire analysis and targeted tumor sequencing of cancer-associated genes. In such studies, assignment of reads to incorrect samples (cross-talk) is a well-documented problem that is rarely considered in practice. By considering unexpected OTUs in artificial (mock) samples, I estimate that cross-talk occurred for ~2% of the reads in one Illumina GAIIx run and eleven Illumina MiSeq runs targeting 16S ribosomal RNA. I also describe UNCROSS, an algorithm for detecting and filtering cross-talk in OTU tables.
Copyright
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