SE132:/DS1
Sample Set Information
ID | SE132 |
---|---|
Title | TargetSearch - a bioconductor package for the efficient preprocessing of GC-MS metabolite profiling data |
Description | We introduce the TargetSearch package, an open source tool which is a flexible and accurate method for pre-processing even very large numbers of GC-MS samples within hours. We developed a novel strategy to iteratively correct and update retention time indices for searching and identifying metabolites. The package is written in the R programming language with computationally intensive functions written in C for speed and performance. The package includes a graphical user interface to allow easy use by those unfamiliar with R.
TargetSearch allows fast and accurate data pre-processing for GC-MS experiments and overcomes the sample number limitations and manual curation requirements of existing software. We validate our method by carrying out an analysis against both a set of known chemical standard mixtures and of a biological experiment. In addition we demonstrate its capabilities and speed by comparing it with other GC-MS pre-processing tools. We believe this package will greatly ease current bottlenecks and facilitate the analysis of metabolic profiling data. |
Authors | Álvaro Cuadros-Inostroza, Camila Caldana, Henning Redestig, Miyako Kusano, Jan Lisec, Hugo Peña-Cortés, Lothar Willmitzer and Matthew A Hannah |
Reference | Cuadros-Inostroza et al. (2009) BMC Bioinformatics 10:428 |
Comment | Total of 27 chromatograms with replicates of three different standard mixtures. Provided for validation of the Bioconductor package.
The raw files were stored in DROP Met as "Mixture Dilution Series for Pre-processing Validation" |
The raw data files are available at DROP Met web site in PRIMe database of RIKEN.
Data Analysis Details Information
ID | DS1 |
---|---|
Title | TargetSearch Standard |
Description | A similar pre-processing analysis as the one described for the standard mixture dataset was performed. We used a fatty acid methyl esters (FAMEs) as RI marker standards (Additional file 8) and an in-house reference library composed of 153 metabolites (Additional file 9). This library was manually curated and in addition to known metabolites includes several unknown metabolites that have been observed in previous experiments.
|
Comment_of_details |