Neuweger Heiko, Albaum Stefan P, Dondrup Michael, Persicke Marcus, Watt Tony, Niehaus Karsten, Stoye Jens, Goesmann Alexander
International NRW Graduate School in Bioinformatics and Genome Research, Bielefeld University, Germany.
Bioinformatics. 2008 Dec 1;24(23):2726-32. doi: 10.1093/bioinformatics/btn452. Epub 2008 Sep 2.
The recent advances in metabolomics have created the potential to measure the levels of hundreds of metabolites which are the end products of cellular regulatory processes. The automation of the sample acquisition and subsequent analysis in high-throughput instruments that are capable of measuring metabolites is posing a challenge on the necessary systematic storage and computational processing of the experimental datasets. Whereas a multitude of specialized software systems for individual instruments and preprocessing methods exists, there is clearly a need for a free and platform-independent system that allows the standardized and integrated storage and analysis of data obtained from metabolomics experiments. Currently there exists no such system that on the one hand supports preprocessing of raw datasets but also allows to visualize and integrate the results of higher level statistical analyses within a functional genomics context.
To facilitate the systematic storage, analysis and integration of metabolomics experiments, we have implemented MeltDB, a web-based software platform for the analysis and annotation of datasets from metabolomics experiments. MeltDB supports open file formats (netCDF, mzXML, mzDATA) and facilitates the integration and evaluation of existing preprocessing methods. The system provides researchers with means to consistently describe and store their experimental datasets. Comprehensive analysis and visualization features of metabolomics datasets are offered to the community through a web-based user interface. The system covers the process from raw data to the visualization of results in a knowledge-based background and is integrated into the context of existing software platforms of genomics and transcriptomics at Bielefeld University. We demonstrate the potential of MeltDB by means of a sample experiment where we dissect the influence of three different carbon sources on the gram-negative bacterium Xanthomonas campestris pv. campestris on the level of measured metabolites. Experimental data are stored, analyzed and annotated within MeltDB and accessible via the public MeltDB web server.
The system is publicly available at http://meltdb.cebitec.uni-bielefeld.de.
代谢组学的最新进展使得测量数百种代谢物水平成为可能，这些代谢物是细胞调节过程的最终产物。能够测量代谢物的高通量仪器中样本采集及后续分析的自动化，给实验数据集的必要系统存储和计算处理带来了挑战。尽管存在众多针对单个仪器的专用软件系统和预处理方法，但显然需要一个免费且独立于平台的系统，以实现对代谢组学实验获得的数据进行标准化和集成化存储与分析。目前还没有这样一个系统，它一方面支持原始数据集的预处理，另一方面又能在功能基因组学背景下可视化并整合更高层次统计分析的结果。
为便于对代谢组学实验进行系统存储、分析和整合，我们开发了MeltDB，这是一个基于网络的软件平台，用于分析和注释代谢组学实验数据集。MeltDB支持开放文件格式（netCDF、mzXML、mzDATA），并有助于整合和评估现有的预处理方法。该系统为研究人员提供了一致描述和存储其实验数据集的方法。通过基于网络的用户界面，向社区提供了代谢组学数据集的全面分析和可视化功能。该系统涵盖了从原始数据到在基于知识的背景下可视化结果的过程，并被集成到比勒费尔德大学基因组学和转录组学现有软件平台的背景中。我们通过一个样本实验展示了MeltDB的潜力，在该实验中我们剖析了三种不同碳源对革兰氏阴性菌野油菜黄单胞菌野油菜致病变种代谢物水平的影响。实验数据在MeltDB中存储、分析和注释，并可通过公共的MeltDB网络服务器访问。
