*library_books*

## Similar protocols

## Protocol publication

[…] The multiplicity of plasmodial infection (MOI, defined as the number of genetically distinguishable parasites per isolate) was estimated for each isolate from the microsatellite locus that exhibited the highest number of alleles. The mean MOI for each collection year of P. falciparum population (1998, 1999, 2002, and 2009) was calculated.The evolution of genetic diversity among Djiboutian P. falciparum populations is dependent on local transmission level and parasite flow, a source of genetic diversity. Genetic diversity was assessed by the Nei unbiased expected heterozygosity index [], He = [n/(n − 1)][1 − Σni = 1p2i] (where n is the number of isolates sampled and pi is the frequency of the ith allele) and calculated from allelic frequencies of five microsatellite loci using GENETIX software version 4.05 []. Pairwise comparisons of He values among the four collection periods were performed using FSTAT software version 2.9.4, with a 10,000 permutations bilateral comparison test [].Genetic similarity of plasmodial populations was investigated using Wright F statistic (FST) []. Pairwise comparisons among the collection years (1998, 1999, 2002, and 2009) were performed based on microsatellite genotype frequencies using FSTAT software version 2.9.4 [,]. FST is a comparison of the sum of genetic variability within and between populations based on the differences in allelic frequencies. FST values were interpreted as no differentiation (0), low genetic differentiation (>0 - 0.05), moderate differentiation (0.05-0.15), and high differentiation (0.15-0.25).Multiple correspondence analyses (MCA), also known as factorial correspondence analysis (FCA) [] according to multilocus genotypes, were conducted to illustrate the genetic similarity of plasmodial populations during the study period. FCA was performed by considering population centroids as active points, using GENETIX software, as described in the help menu []. The graphical representation with 95% data concentration ellipse (i e, including 95% of the projected genotypes on the FCA plan) and centroids was obtained using R software, version R 2.15.1 [].The relationships between parasite genotypes were assessed using **eBurst** algorithm. Based on microsatellite allelic profiles, the algorithm selects the most parsimonious patterns of genotype evolution and predicts founder(s). The assignment of founders is tested by a bootstrap procedure []. The global optimization of the diagram based on goeBurst algorithm [] was performed with **Phyloviz** software []. The eBurst algorithm implements a simple model of clonal expansion and diversification which is generally used to represent a population of clonal prokaryote []. Despite its obligatory sexual stage, P. falciparum may evolve as a clonal organism due to inbreeding [,-]. A high self-fertilization rate (i.e. syngamy between genetically identical gametes) may be favoured in low malaria transmission settings [,,,]. Outbreaks are an extreme situation where the oligo-clonal spreading of parasites (i e, only few plasmodial populations propagate during epidemics) may occur [-]. As malaria epidemics had occurred in Djibouti with oligo-clonal expansion of plasmodial populations [,], eBurst diagram is particularly well adapted for the description of Djiboutian malaria situation.Comparison between the global unstratified eBurst diagram and eBurst diagram stratified by the sampling year was performed to assess the robustness of eBurst algorithm.The index of discriminatory power (D) was assessed in order to estimate the discriminatory power of the genotyping based on four microsatellite loci. This index is calculated from the number of genotypes and their relative frequencies. The index D is the probability that two unrelated parasites randomly sampled from studied population display different genotypes. By analogy with Nei unbiased expected heterozygosity index (He), D is an indirect measure of genotypic diversity. According to Hunter and Gaston’s formula [], D = 1 − 1/(N(N − 1)) ΣSj = 1nj(nj − 1) where N is the total number of parasites in the sample population, s is the total number of genotypes observed, and nj is the number of strains with the jth genotype. […]

## Pipeline specifications

Software tools | BURST, PHYLOViZ |
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Applications | Phylogenetics, WGS analysis |

Organisms | Plasmodium falciparum |

Diseases | Infection, Malaria |

Chemicals | Pyrimethamine |