An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

Spatio-temporal modelling of environmental data

Programa Doutoral em Matemática e Aplicações.

Assessment of distinctive road runoff quality in coastal areas, based on a monitoring case study

High levels of marine salt deposition present in coastal areas have a relevant effect on road runoff characteristics. This study assesses this effect with the purpose of identifying the relationships between monitored water quality parameters and intrinsic site variables. To achieve this objective, an extensive monitoring program was conducted on a Portuguese coastal highway. The study included 30 rainfall events, in different weather, traffic, and salt deposition conditions. The evaluations of various water quality parameters were carried out in over 200 samples. In addition, the meteorological, hydrological, and traffic parameters were continuously measured. The salt deposition rates were determined by means of a wet candle device, which is an innovative feature of the monitoring program. The relation between road runoff pollutants and independent variables associated with weather, traffic, and salt deposition conditions was assessed. Significant correlations among pollutants were observed. A high salinity concentration and its influence on the road runoff were confirmed. Furthermore, the concentrations of the most relevant pollutants seemed to be very dependent on some meteorological variables, particularly the duration of the antecedent dry period prior to each rainfall event and the average wind speed.