RESUMO De acordo com estudos realizados, cerca de 10 milhões de pessoas desenvolveram tuberculose em 2018. Desse total, 1,5 milhão de pessoas morreram devido à doença. Procurando estudar o comportamento das sequências do genoma da Mycobacteruim tuberculosis (MTB), bactéria responsável por desenvolver a Tuberculose (TB), foi realizada uma análise aplicando o k-mer (frequência de palavras do DNA). Os valores de k variaram de 1 a 10, pois devido a análise ter sido feita no comprimento total das sequencias, onde cada sequencia é composta por aproximadamente 4 milhões de pares de bases, valores de k acima de 10, a análise é interrompida, como consequência da capacidade do programa. O intuito do trabalho foi de verificar a formação da árvore filogenética em cada k-mer analisado. Os resultados obtidos evidenciaram a formação de grupos distintos em alguns k-mers analisados, levando-se em consideração a linha de corte. Entretanto, em todos os grupos formados as cepas multidroga resistente (MDR) e extensivamente resistente à droga (XDR) permaneceram juntas e separadas das demais cepas.

Abstract According to studies carried out, approximately 10 million people developed tuberculosis in 2018. Of this total, 1.5 million people died from the disease. To study the behavior of the genome sequences of Mycobacterium tuberculosis (MTB), the bacterium responsible for the development of tuberculosis (TB), an analysis was performed using k-mers (DNA word frequency). The k values ranged from 1 to 10, because the analysis was performed on the full length of the sequences, where each sequence is composed of approximately 4 million base pairs, k values above 10, the analysis is interrupted, as consequence of the program's capacity. The aim of this work was to verify the formation of the phylogenetic tree in each k-mer analyzed. The results showed the formation of distinct groups in some k-mers analyzed, taking into account the threshold line. However, in all groups, the multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains remained together and separated from the other strains.

Abstract The classifications resulting from phylogenetic analysis are essential tools for evolutionary studies. Phylogenetic is more than a part of evolutionary biology because its underlying philosophy provides a way to see nature, ask questions, and solve problems related to the evolution of organisms. Given the importance of phylogeny, our aim was to devise a method to assess the delimitation of bacterial species. We used the non-decimated discrete wavelet transform. The wavelet function used was Daubechies’ with four null moments, considering seven, four and two decomposition levels. For clustering, the energy (variance) obtained at each level of decomposition and the Mahalanobis distance was used to visualize the dendrogram formation process. Through the analysis, we verified that the gram-positive bacteria were classified well into their respective species, but most gram-negative bacteria did not take into account the more significant amount of energy obtained in scenario two. According to the results, the energy plays an important role in the delimitation of groups of bacterial species.

RESUMO Objetivo Verificar se existe relação de similaridade entre o número de suicídio em países desenvolvidos e emergentes usando a técnica de ondaletas. Métodos Os dados anuais foram obtidos a partir do relatório da Organização Mundial da Saúde (OMS), no período de 1986 a 2015. Para análise, foi empregada a transformada discreta não decimada de ondaleta (NDWT), a função ondaleta aplicada foi a Daubechies com cinco níveis de decomposição. Com relação ao agrupamento, utilizou-se a energia (variância) para analisar os clusters e, para a visualização do processo de clusterização, trabalhamos com o dendograma, no qual se empregou a distância de Mahalanobis. A quantidade de grupos foi definida por meio da função NbCluster. Resultados A partir da análise de cluster , verificou-se a formação de quatros grupos. No qual, Japão e Estados Unidos e Brasil localizam-se em grupos distintos e isolados. E os demais países (Áustria, Bélgica, Chile, Israel, México, Itália e Holanda) em um único grupo. Conclusão Utilizando esse método, foi possível verificar com mais detalhes quais países apresentaram comportamentos semelhantes, mesmo apresentando características bem distintas entre si, tanto socioeconômica, geográfica e climática.

ABSTRACT Objective The aim of this study was to use a wavelet technique to determine whether the number of suicides is similar between developed and emerging countries. Methods Annual data were obtained from World Health Organization (WHO) reports from 1986 to 2015. Discrete nondecimated wavelet transform was used for the analysis, and the Daubechies wavelet function was applied with five-level decomposition. Regarding clustering, energy (variance) was used to analyze the clusters and visualize the clustering process. We constructed a dendrogram using the Mahalanobis distance. The number of groups was set using a specific function in the R program. Results The cluster analysis verified the formation of four groups as follows: Japan, the United States and Brazil were distinct and isolated groups, and other countries (Austria, Belgium, Chile, Israel, Mexico, Italy and the Netherlands) constituted a single group. Conclusion The methods utilized in this paper enabled a detailed verification of countries with similar behaviors despite very distinct socioeconomic, geographic and climate characteristics.

Abstract INTRODUCTION: Tuberculosis is listed among the top 10 causes of deaths worldwide. The resistant strains causing this disease have been considered to be responsible for public health emergencies and health security threats. As stated by the World Health Organization (WHO), around 558,000 different cases coupled with resistance to rifampicin (the most operative first-line drug) have been estimated to date. Therefore, in order to detect the resistant strains using the genomes of Mycobacterium tuberculosis (MTB), we propose a new methodology for the analysis of genomic similarities that associate the different levels of decomposition of the genome (discrete non-decimated wavelet transform) and the Hurst exponent. METHODS: The signals corresponding to the ten analyzed sequences were obtained by assessing GC content, and then these signals were decomposed using the discrete non-decimated wavelet transform along with the Daubechies wavelet with four null moments at five levels of decomposition. The Hurst exponent was calculated at each decomposition level using five different methods. The cluster analysis was performed using the results obtained for the Hurst exponent. RESULTS: The aggregated variance, differenced aggregated variance, and aggregated absolute value methods presented the formation of three groups, whereas the Peng and R/S methods presented the formation of two groups. The aggregated variance method exhibited the best results with respect to the group formation between similar strains. CONCLUSION: The evaluation of Hurst exponent associated with discrete non-decimated wavelet transform can be used as a measure of similarity between genome sequences, thus leading to a refinement in the analysis.

Abstract We propose to evaluate genome similarity by combining discrete non-decimated wavelet transform (NDWT) and elastic net. The wavelets represent a signal with levels of detail, that is, hidden components are detected by means of the decomposition of this signal, where each level provides a different characteristic. The main feature of the elastic net is the grouping of correlated variables where the number of predictors is greater than the number of observations. The combination of these two methodologies applied in the clustering analysis of the Mycobacterium tuberculosis genome strains proved very effective, being able to identify clusters at each level of decomposition.