DataSheet1.CSV

Abstract

Gene expression profiling techniques, such as DNA microarray and RNA-Sequencing, have provided a significant impact on our understanding of biological systems. It contributes to almost all aspects of biomedical research, including studying developmental biology, disease progression, drug effects, and host-parasite relationships. However, the high-throughput data generation presents a challenge for many wet experimentalists to analyze and take full advantage of such rich and complex data. Here we present GeneCloudOmics, an easy-to-use web server for gene expression and protein datasets analysis and visualization. GeneCloudOmics allows both microarray or RNA-Seq data analysis with a comprehensive range of data analytics tools in one package that no other current standalone software or web-based tool can do. In total, GeneCloudOmics provides user access to 23 different data analytics and bioinformatics tasks including reads normalization, scatter plots, linear/non-linear correlations, PCA, clustering (hierarchical, k-means, t-SNE, SOM), differential expression analyses, pathways enrichments, evolutionary analyses, pathological analyses and protein-protein interaction (PPI) identifications. The user performs all tasks through an intuitive graphical user interface (GUI) that overcomes the hassle of coding, installing tools/packages/libraries and dealing with operating systems compatibility and version issues, complications that make data analysis tasks challenging for biologists. GeneCloudOmics is a one-stop open-source tool for gene exprerssion data analysis and visualization and is freely available at http://combio-sifbi.org/GeneCloudOmics.