bistro: An R package for vector bloodmeal identification by short tandem repeat overlap

bistro:通过短串联重复重叠识别载体血粉的 R 包

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作者:Zena Lapp, Lucy Abel, Judith Mangeni, Andrew A Obala, Wendy P O'Meara, Steve M Taylor, Christine F Markwalter

Abstract

Measuring vector-human contact in a natural setting can inform precise targeting of interventions to interrupt transmission of vector-borne diseases. One approach is to directly match human DNA in vector bloodmeals to the individuals who were bitten using genotype panels of discriminative short tandem repeats (STRs). Existing methods for matching STR profiles in bloodmeals to the people bitten preclude the ability to match most incomplete profiles and multi-source bloodmeals to bitten individuals.We developed bistro, an R package that implements 3 preexisting STR matching methods as well as the package's namesake, bistro, a new algorithm described here. bistro employs forensic analysis methods to calculate likelihood ratios and match human STR profiles in bloodmeals to people using a dynamic threshold. We evaluated the algorithm's accuracy and compared it to existing matching approaches using a publicly-available panel of 188 single-source and 100 multi-source samples containing DNA from 50 known human sources. Then we applied it to match 777 newly field-collected mosquito bloodmeals to a database of 645 people.The R package implements four STR matching algorithms in user-friendly functions with clear documentation. bistro correctly matched 99% (187/188) of profiles in single-source samples, and 62% (224/359) of profiles from multi-source samples, resulting in a sensitivity of 0.75 (vs < 0.51 for other algorithms). The specificity of bistro was 0.9998 (vs. 1 for other algorithms). Furthermore, bistro identified 79% (720/906) of all possible matches for field-derived mosquitoes, yielding 1.4x more matches than existing algorithms.bistro identifies more correct bloodmeal-human matches than existing approaches, enabling more accurate and robust analyses of vector-human contact in natural settings. The bistro R package and corresponding documentation allow for straightforward uptake of this algorithm by others.

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