PT - JOURNAL ARTICLE AU - Angela M. Early AU - Rachel F. Daniels AU - Timothy M. Farrell AU - Sarah K. Volkman AU - Dyann F. Wirth AU - Bronwyn L. MacInnis AU - Daniel E. Neafsey TI - Amplicon deep sequencing of low-density <em>Plasmodium falciparum</em> infections: an evaluation of analysis approaches AID - 10.1101/453472 DP - 2018 Jan 01 TA - bioRxiv PG - 453472 4099 - http://biorxiv.org/content/early/2018/10/25/453472.short 4100 - http://biorxiv.org/content/early/2018/10/25/453472.full AB - Background: Deep sequencing of targeted genomic regions is becoming a common tool for understanding the dynamics and complexity of Plasmodium infections. Here, Illumina-based amplicon sequencing of two P. falciparum genomic regions (CSP and SERA2) was performed on two types of samples: in vitro DNA mixtures mimicking low-density infections (1-200 genomes/μl) and natural patient samples (44-653,080 parasites/μl). The analytical performance of four analysis tools—PASEC, DADA2, HaplotypR, and SeekDeep—was compared on both datasets.Results: All four analysis tools were able to contend with mock low-density samples, showing reasonable detection accuracy down to a concentration of 5 Plasmodium genome copies/μl. Due to increased stochasticity and background noise, however, accuracy was reduced for samples with very low parasitemia (&lt; 5 copies/μl) or very low read count (&lt;100 reads per amplicon). PASEC could distinguish major vs. minor haplotypes with an accuracy of 90% in samples with at least 30 Plasmodium genome copies/μl, but only 61% at low Plasmodium concentrations (&lt; 5 copies/μl) and 46% at low read counts (&lt;25 reads per amplicon). The four tools were additionally compared on a panel of patient samples, and all four provided concordant complexity of infection patterns across four sub-Saharan African countries.Conclusions: Amplicon deep sequencing successfully determines the complexity and diversity of low-density Plasmodium infections, even in the absence of technical PCR/sequencing replicates. Current state-of-the-art tools offer multiple robust approaches for analyzing amplicon data. However, as samples with very low parasitemia and very low read count have higher false positive rates, researchers should consider implementing higher read count thresholds when working with low-density samples.