Quality-filtering Vastly Improves Diversity Estimates from Illumina Amplicon Sequencing

A systematic evaluation of parameters that affect short amplicons sequenced on Illumina platforms provides guidelines for how to eliminate erroneous reads and improve data interpretation. High-throughput sequencing has revolutionized microbial ecology, but read quality remains a considerable barrier to accurate taxonomy assignment and α-diversity assessment for microbial communities. We demonstrate that high-quality read length and abundance are the primary factors differentiating correct from erroneous reads produced by Illumina GAIIx, HiSeq and MiSeq instruments. We present guidelines for user-defined quality-filtering strategies, enabling efficient extraction of high-quality data and facilitating interpretation of Illumina sequencing results.