MIAME Based Method Design And Practice For Integration Of Gene Expression Data

With the development of Molecular Biology, large amounts of molecular biological data have exploded which produces large number of public molecular biological data sources.Through these public data sources, researchers can get all kinds of molecular biological data from different data sources to make further use of the data and explore the biological significance in these data. However, it’s heterogeneous among the data from different data sources while researchers have to spend much time and energy for data processing. This is a current problem needed to be resolved, which is a big challenge for study.Gene expression data is the important part of molecular biological data, while GEO that use SOFT format to store gene expression data and ArrayExpress that use MAGE-TAB format to store gene expression data are the two main public database of gene expression data all over the world. There is a big difference between SOFT and MAGE-TAB in data format definition, which makes it difficult for researchers to use data from GEO and ArrayExpress for further data analysis and biomedical research directly.In response to these problems, the goal of this paper is about integrated approach of gene expression data. In 2001, FGED associations have established Minimum Information About a Microarray Experiment (MIAME) to define the content required for gene expression data. According to the fact that SOFT and MAGE-TAB are based on MIAME, the main idea of this paper is to establish mapping relationship for several gene expression data formats and exchange data from different gene expression data formats, based on MIAME. Details are as follows:Analyze MIAME, SOFT and MAGE-TAB.Analyze the experimental information and raw data, two parts of the gene expression data.Establish the integrated approach for experimental information. Setting MAGE-TAB as the standard and building the mapping relationship from SOFT to MAGE-TAB.Establish the integrated approach for raw data. Setting Agilent as main and GenePix and Affymetrix as supplemented for the standard and building mapping relationship from three chip data format to the standard format.According to integrated approach of this paper, develop the tool for data conversion and achieve the conversion for different format data.The effectiveness of the integrated approach for gene expression data in this paper is validated by data conversion through real data, which provide a feasible solution for integration of gene expression data.