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

作者：Shani Ben-Ari Fuchs, Iris Lieder, Gil Stelzer, Yaron Mazor, Ella Buzhor, Sergey Kaplan, Yoel Bogoch, Inbar Plaschkes, Alina Shitrit, Noa Rappaport, Asher Kohn, Ron Edgar, Liraz Shenhav, Marilyn Safran, Doron Lancet, Yaron Guan‐Golan, David Warshawsky, Ronit Shtrichman · 发表于：OMICS A Journal of Integrative Biology · 年份：2016 · DOI：10.1089/omi.2015.0168 · 被引用次数：280 · 研究领域：Bioinformatics and Genomic Networks、Gene expression and cancer classification、Genomics and Phylogenetic Studies

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...