GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data

TLDR

Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine, and gene set enrichment tools are emerging remedies to this challenge. The study introduces GeneAnalytics™, a comprehensive, easy‑to‑apply gene set analysis tool designed to rapidly contextualize expression patterns and functional signatures from postgenomics Big Data domains such as NGS, RNAseq, and microarray experiments, addressing the limited understanding of biological and clinical contexts that hampers data‑to‑knowledge translation. GeneAnalytics leverages LifeMap Science’s GeneCards, MalaCards, and PathCards databases, uses evidence‑based scoring algorithms and an intuitive interface, and incorporates LifeMap Discovery’s curated expression data for normal and diseased tissues to enable advanced gene‑tissue association matching. The tool assists in evaluating differentiation protocols and discovering tissue‑ and cell‑specific biomarkers, with results directly linked to gene, disease, or cell cards in the GeneCards suite.

Abstract

Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from "data-to-knowledge-to-innovation," a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ (geneanalytics.genecards.org), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®—the human gene database; the MalaCards—the human diseases database; and the PathCards—the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®—the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene–tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell "cards" in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics, and others yet to emerge on the postgenomics horizon.