ABSTRACT
SUMMARY: Data processing, analysis and visualization (datPAV) is an exploratory tool that allows experimentalist to quickly assess the general characteristics of the data. This platform-independent software is designed as a generic tool to process and visualize data matrices. This tool explores organization of the data, detect errors and support basic statistical analyses. Processed data can be reused whereby different step-by-step data processing/analysis workflows can be created to carry out detailed investigation. The visualization option provides publication-ready graphics. Applications of this tool are demonstrated at the web site for three cases of metabolomics, environmental and hydrodynamic data analysis. AVAILABILITY: datPAV is available free for academic use at http://www.sdwa.nus.edu.sg/datPAV/.
Subject(s)
Computer Graphics , Software , Metabolomics , User-Computer Interface , WorkflowABSTRACT
SUMMARY: Analysis of high throughput metabolomics experiments is a resource-intensive process that includes pre-processing, pre-treatment and post-processing at each level of experimental hierarchy. We developed an interactive user-friendly online software called Metabolite Data Analysis Tool (MetDAT) for mass spectrometry data. It offers a pipeline of tools for file handling, data pre-processing, univariate and multivariate statistical analyses, database searching and pathway mapping. Outputs are produced in the form of text and high-quality images in real-time. MetDAT allows users to combine data management and experiment-centric workflows for optimization of metabolomics methods and metabolite analysis. AVAILABILITY: MetDAT is available free for academic use from http://smbl.nus.edu.sg/METDAT2/. CONTACT: sanjay@nus.edu.sg
Subject(s)
Mass Spectrometry/methods , Metabolomics/methods , Software , Database Management Systems , Databases, Factual , Electronic Data Processing , WorkflowABSTRACT
The aim of metabolomics is to identify, measure, and interpret complex time-related concentration, activity, and flux of metabolites in cells, tissues, and biofluids. We have used a metabolomics approach to study the biochemical phenotype of mammalian cells which will help in the development of a panel of early stage biomarkers of heat stress tolerance and adaptation. As a first step, a simple and sensitive mass spectrometry experimental workflow has been optimized for the profiling of metabolites in rat tissues. Sample (liver tissue) preparation consisted of a homogenization step in three different buffers, acidification with different strengths of acids, and solid-phase extraction using nine types of cartridges of varying specificities. These led to 18 combinations of acids, cartridges, and buffers for testing for positive and negative ions using mass spectrometry. Results were analyzed and visualized using algorithms written in MATLAB v7.4.0.287. By testing linearity, repeatability, and implementation of univariate and multivariate data analysis, a robust metabolomics platform has been developed. These results will form a basis for future applications in discovering metabolite markers for early diagnosis of heat stress and tissue damage.
