# Spoligotype Database of Mycobacterium tuberculosis: Biogeographic Distribution of Shared Types and Epidemiologic and Phylogenetic Perspectives

Christophe Sola* , Ingrid Filliol*, Maria Cristina Gutierrez†, Igor Mokrousov*, Véronique Vincent†, and Nalin Rastogi*
Author affiliations: *Institut Pasteur de Guadeloupe, Pointe à Pitre, Guadeloupe; †Centre National de Référence des Mycobactéries, Institut Pasteur, Paris, France

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## Figure 1

Figure 1. . Histograms derived from database (online) summarizing the distribution of shared types (A), their respective sizes (B), and their relative distribution in different locations (C).

Main Article

1For this purpose, the independent sampling sizes for Europe and the USA were taken as n1 and n2, the number of individuals within a given shared-type "x" was k1 and k2, and in this case, the representativeness of the two samples was p1=k1/n1 and P2=k2/n2, respectively. To assess if the divergence observed between p1 and p2 was due to sampling bias or the existence of two distinct populations, the percentage of individuals (p0) harboring shared-type "x" in the population studied was estimated by the equation p0= k1+k2/n1+n2=n1p1+n2p2/n1+n2. The distribution of the percentage of shared-type "x" in the sample sizes n1 and n2 follows a normal distribution with a mean p0 and a standard deviation of and respectively, and the difference d=p1-p2 follows a normal distribution of mean p0-p0=0 and of variance σd2p12p22 = p0q0/n1+p0q0/n2 or σd2=p0q0 (1/n1+1/n2). The two samples being independent, the two variances were additive; the standard deviation σd= was calculated, and the homogeneity of the samples tested was assessed using the quotient d/σd=p1-p2/. If the absolute value of the quotient d/σd<2, the two samples were considered to belong to a same population (CI 95%) and the variation observed in the distribution of isolates for given shared types could be due to a sampling bias. Inversely, if d/σd>2, then the differences observed in the distribution of isolates for given shared types were statistically significant and not due to potential sample bias.

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