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. 2020 Aug 6;10:13296. doi: 10.1038/s41598-020-69921-z

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Performance of combined Human Chagas-Flow ATE-IgG1 for DTU-specific diagnosis of Chagas disease. (A) Principal component (PC) analysis of defined sets of attributes (“TI 4,000/50%”, “EI 2,000/50%”, “AVI 8,000/60%” and “TVI 4,000/50%”) were able to segregate sera samples from Chagas disease patients infected with distinct DTUs. Two population prototypes, referred as “TcI vs TcVI vs TcII” and “TcI vs TcII” were tested to illustrate the distribution of human T. cruzi infection in distinct geographic regions within the endemic area. Data are expressed as individual scores for PC1 and PC2. (B) Decision tree algorithms were built for DTU-specific diagnostic purposes for both population prototypes using the selected sets of attributes (“target-antigen/serum dilution/cut-off”). The global accuracy and leave-one-out-cross-validation (LOOCV) scores are provided in the Figure.