Browsing by Author "Nascimento, Marta"
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- Distance-based phylogenetic inference from typing data: a unifying viewPublication . Vaz, Cátia; Nascimento, Marta; Carrico, Joao; Rocher, Tatiana; Francisco, Alexandre P.Typing methods are widely used in the surveillance of infectious diseases, outbreaks investigation and studies of the natural history of an infection. Moreover, their use is becoming standard, in particular with the introduction of high-throughput sequencing. On the other hand, the data being generated are massive and many algorithms have been proposed for a phylogenetic analysis of typing data, addressing both correctness and scalability issues. Most of the distance-based algorithms for inferring phylogenetic trees follow the closest pair joining scheme. This is one of the approaches used in hierarchical clustering. Moreover, although phylogenetic inference algorithms may seem rather different, the main difference among them resides on how one defines cluster proximity and on which optimization criterion is used. Both cluster proximity and optimization criteria rely often on a model of evolution. In this work, we review, and we provide a unified view of these algorithms. This is an important step not only to better understand such algorithms but also to identify possible computational bottlenecks and improvements, important to deal with large data sets.
- Dynamic phylogenetic inference for sequence-based typing dataPublication . Francisco, Alexandre; Nascimento, Marta; Vaz, CátiaTyping methods are widely used in the surveillance of infectious diseases, outbreaks investigation and studies of the natural history of an infection. And their use is becoming standard, in particular with the introduction of High Throughput Sequencing (HTS). On the other hand, the data being generated is massive and many algorithms have been proposed for phylogenetic analysis of typing data, such as the goeBURST algorithm. These algorithms must however be run whenever new data becomes available starting from scratch. We address this issue proposing a dynamic version of goeBURST algorithm. Experimental results show that this new version is efficient on integrating new data and updating inferred evolutionary patterns, improving the update running time by at least one order of magnitude.
- Dynamic phylogenetic inference for sequence-based typing dataPublication . Francisco, Alexandre P.; Nascimento, Marta; Vaz, CátiaTyping methods are widely used in the surveillance of infectious diseases, outbreaks investigation and studies of the natural history of an infection. And their use is becoming standard, in particular with the introduction of High Throughput Sequencing (HTS). On the other hand, the data being generated is massive and many algorithms have been proposed for phylogenetic analysis of typing data, such as the goeBURST algorithm. These algorithms must however be run whenever new data becomes available starting from scratch. We address this issue proposing a dynamic version of goeBURST algorithm. Experimental results show that this new version is efficient on integrating new data and updating inferred evolutionary patterns, improving the update running time by at least one order of magnitude.
- PHYLOViZ 2.0: providing scalable data integration and visualization for multiple phylogenetic inference methodsPublication . Nascimento, Marta; Sousa, Adriano; Ramirez, Mario; Francisco, Alexandre; Carrico, Joao; Vaz, CátiaHigh Throughput Sequencing provides a cost effective means of generating high resolution data for hundreds or even thousands of strains, and is rapidly superseding methodologies based on a few genomic loci. The wealth of genomic data deposited on public databases such as Sequence Read Archive/European Nucleotide Archive provides a powerful resource for evolutionary analysis and epidemiological surveillance. However, many of the analysis tools currently available do not scale well to these large datasets, nor provide the means to fully integrate ancillary data. Here we present PHYLOViZ 2.0, an extension of PHYLOViZ tool, a platform independent Java tool that allows phylogenetic inference and data visualization for large datasets of sequence based typing methods, including Single Nucleotide Polymorphism ( SNP) and whole genome/core genome Multilocus Sequence Typing (wg/cgMLST) analysis. PHYLOViZ 2.0 incorporates new data analysis algorithms and new visualization modules, as well as the capability of saving projects for subsequent work or for dissemination of results.