Researchers from Taiwan have developed a tool to analyse the metabolomics data. The report describing this tool was recently published in Analytical chemistry. Its called as SMART – Statistical Metabolomics Analysis-An R Tool.
Metabolomics is the large-scale study of small molecules, commonly known as metabolites, within cells, biofluids, tissues or organisms. Collectively, these small molecules and their interactions within a biological system are known as the metabolome.
Metabolomics data provide unprecedented opportunities to decipher metabolic mechanisms by analyzing hundreds to thousands of metabolites. Data quality concerns and complex batch effects in metabolomics must be appropriately addressed through statistical analysis.
SMART has been developed by a group of researchers in Institute of Statistical Science, Academia Sinica, Taipei led by Dr. Pan Wen Harn and Dr. Hsin-Chou Yang. The team has developed an integrated analysis tool for metabolomics studies to streamline the complete analysis flow from initial data pre-processing to downstream association analysis.
SMART written in R and R GUI has been developed as user-friendly software for integrated analysis of metabolomics data. It can analyze input files with different formats. Thereafter, SMART streamlines the complete analysis flow from initial data pre-processing to downstream association analysis:
- Analysis of different data file formats (e.g., .raw, .d, and mzXML)
- Visually representing various types of data features (e.g., total ion chromatogram and mass spectra)
- Implementing peak alignment
- Conducting quality control for samples and peaks
- Exploring batch effects (e.g., known experimental conditions, unknown latent groups, or hidden substructures)
- Performing association analysis.
Sounds awesome? Go ahead and give SMART a try!
If you wish to use this tool for your research, you can cite it as follows:
Yu-Jen Liang, Yu-Ting Lin, Chia-Wei Chen, Chien-Wei Lin, Kun-Mao Chao, Wen-Harn Pan and Hsin-Chou Yang (2016/05). SMART: Statistical Metabolomics Analysis – An R Tool. Analytical Chemistry
Any further correspondence can be addressed to:
Dr. Hsin-Chou Yang, Institute of Statistical Science, Academia Sinica, 128, Academia Road, Section 2 Nankang, Taipei 115, Taiwan. (Fax) 886-2-27831523; (Tel) 886-2-27889311 ext. 113; (E-mail) email@example.com