PDF(Pubmed)
Abstract：
Microarray experiments, a mainstay in gene expression analysis for nearly two decades, pose challenges due to their complexity. To address this, we introduce DExplore, a user-friendly web application enabling researchers to detect differentially expressed genes using data from NCBI\'s GEO. Developed with R, Shiny, and Bioconductor, DExplore integrates WebGestalt for functional enrichment analysis. It also provides visualization plots for enhanced result interpretation. With a Docker image for local execution, DExplore accommodates unpublished data. To illustrate its utility, we showcase two case studies on cancer cells treated with chemotherapeutic drugs. DExplore streamlines microarray data analysis, empowering molecular biologists to focus on genes of biological significance.
摘要：
微阵列实验,近二十年来一直是基因表达分析的支柱，由于它们的复杂性而构成挑战。为了解决这个问题，我们介绍DExplore，一个用户友好的网络应用程序，使研究人员能够使用NCBI的GEO数据检测差异表达的基因。用R开发,闪亮，和生物导体，DExplore集成了WebGestalt以进行功能丰富分析。它还提供了用于增强结果解释的可视化图。使用用于本地执行的Docker映像，DExplore可容纳未发布的数据。为了说明它的效用，我们展示了两个用化疗药物治疗的癌细胞的案例研究。DExplore流线微阵列数据分析,使分子生物学家能够专注于具有生物学意义的基因。
