Introduction to gene expression profiling tool

Gene expression profiling is a powerful tool for pathogenetic studies of complex diseases. To remedy the defect of traditional single gene expression analysis, various genehttp://www.cusabio.com/catalog-13-1.html set expression analysis (GSEA) approaches were proposed and sucessfully applied in the microarray studies of complex diseases. GSEA is able to identify diseases relevant biological pathways that are difficult to be detected using single gene expression analysis. Because of simultaneously considering the expression levels and biological effects of multiple functionally related genes, GSEA is powerful and has the potential to provide additional insight into the pathogenesis of complex diseases. Expression quantitative trait loci (eQTLs) are genomic polymorphism loci (for instance SNPs), which can regulate gene expression levels. Through genome-wide detecting associations between gene transcript abundance and genomic polymorphisms, a large number of eQTLs has been identified in human genome. Given the significant impact of eQTLs on gene expression profiles, it is interesting to conduct joint pathway analysis of microarray and eQTLs data. Furthermore, it is well known that microarray studies suffered from the impact of confounding factors, such asenvironmental and technical factors, causing unreliable feature selection and high false negative rates. Jointly analyzing microarray and eQTLs data may help to reduce bias in micorarray data and increase statistical power. However, to the best of our knowledge, few efforts have been paied for implementing joint pathway analysis of micorarray and eQTLs datahttp://www.cusabio.com/catalog-13-1.html. Kashin-Beck disease (KBD) is a serious osteoarthropathia, affecting more than 2.5 million people in China. Excessive chondrocyte apoptosis is one of the primary cartilage damage of KBD. Although extensive studies had been conducted in the past decades, the pathogenesis of excessive chondrocyte apoptosis of KBD remains unclear, resulting in the lack of effective treatments for KBD now. For instance, the prevalence of KBD in children reached 50.43% and 32.93% at the prevalent areas of Tibet and Shaanxi province of China. We recently conducted a microarray study of KBD and identified a set of abnormally expressed genes in KBD articular cartilage. 1,717 Han Chinese subjects were also genotyped using Affymetrix Genome Wide Human SNP Array 6.0. Affymetrix Genome Wide Human SNP Array 6.0 contains more than 906,600 SNPs probes, which provide genome-wide eQTLs data of KBD for this study. To improve the performance of pathway-based gene expression profile studies, we proposed an eQTL-weighted pathway expression analysis (EPEA) approach in this study. Using the genome-wide microarray and eQTLs data of KBD, EPEA was performed to identify KBD relevant biological pathways. A program EPEA developed by C and R languages was also provided for joint pathway analysis of genome-wide microarray and eQTLs data. Extended reading:http://www.cusabio.com/ELISA-Kit/Human-enterovirus-71-virus-EV71-antibody-IgG-ELISA-kit-1042008.html