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- Bouakaze, Caroline, et al.
(författare)
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Predicting haplogroups using a versatile machine learning program (PredYMaLe) on a new mutationally balanced 32 Y-STR multiplex (CombYplex) : Unlocking the full potential of the human STR mutation rate spectrum to estimate forensic parameters
- 2020
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Ingår i: Forensic Science International. - : Elsevier BV. - 1872-4973 .- 1878-0326. ; 48
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Tidskriftsartikel (refereegranskat)abstract
- We developed a new mutationally well-balanced 32 Y-STR multiplex (CombYplex) together with a machine learning (ML) program PredYMaLe to assess the impact of STR mutability on haplogourp prediction, while respecting forensic community criteria (high DC/HD). We designed CombYplex around two sub-panels M1 and M2 characterized by average and high-mutation STR panels. Using these two sub-panels, we tested how our program PredYmale reacts to mutability when considering basal branches and, moving down, terminal branches. We tested first the discrimination capacity of CombYplex on 996 human samples using various forensic and statistical parameters and showed that its resolution is sufficient to separate haplogroup classes. In parallel, PredYMaLe was designed and used to test whether a ML approach can predict haplogroup classes from Y-STR profiles. Applied to our kit, SVM and Random Forest classifiers perform very well (average 97 %), better than Neural Network (average 91 %) and Bayesian methods (< 90 %). We observe heterogeneity in haplogroup assignation accuracy among classes, with most haplogroups having high prediction scores (99-100 %) and two (E1b1b and G) having lower scores (67 %). The small sample sizes of these classes explain the high tendency to misclassify the Y-profiles of these haplogroups; results were measurably improved as soon as more training data were added. We provide evidence that our ML approach is a robust method to accurately predict haplogroups when it is combined with a sufficient number of markers, well-balanced mutation rate Y-STR panels, and large ML training sets. Further research on confounding factors (such as CNV-STR or gene conversion) and ideal STR panels in regard to the branches analysed can be developed to help classifiers further optimize prediction scores.
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| 2. |
- Courtin, David, et al.
(författare)
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G6PD A-variant influences the antibody responses to Plasmodium falciparum MSP2.
- 2011
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Ingår i: Infection, Genetics and Evolution. - : Elsevier BV. - 1567-1348 .- 1567-7257. ; 11:6, s. 1287-1292
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Tidskriftsartikel (refereegranskat)abstract
- High antibody levels directed to Plasmodium falciparum merozoite surface proteins (MSP), including MSP2, as well as genetically related red blood cell defects, have previously been found to be associated with protection against malaria. Here, our main objective was to study the changes in MSP2-specific total IgG, IgG1 and IgG3 responses during a malaria transmission season in order to assess the impact of sickle-cell, α(+)-thalassemia and G6PD variants on antibody kinetics. Repeated parasitological assessments of a cohort of children were conducted during an 8-month period. Antibody responses to recombinant MSP2/3D7 and MSP2/FC27 proteins were measured at the beginning and at the end of transmission season. We found that (i) the period of last Plasmodium falciparum infection during the transmission season was associated with IgG3 anti-MSP2 change. Compared to the IgG3 levels of children infected in January 2003 (end of transmission season), the IgG3 level of children decreased with the length of the period without infection, (ii) G6PD A- carriers had a lower increase of IgG3 levels to MSP2/FC27 and MSP2/3D7 during the transmission season than the noncarriers. This latter finding is suggestive of qualitative and/or quantitative reduction of exposure to malarial antigens related to this genetic variant, leading to weaker stimulation of specific antibody responses. We speculate that cell-mediated immune activity may explain the clinical protection afforded by this genetic trait.
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