(by Rolando Garcia Milian)
Qlucore Omics Explorer facilitates a dynamic, visualization-guided analysis of OMICs data, applicable to various phases of a discovery cycle. What differentiates Qlucore is the combination of speed, advanced analytics, seamless workflow, and simplicity. With Qlucore you can visualize, QC, apply statistics, and create publication-ready graphics, such as 3D Principal Component Analysis, heat maps, and various 2D plots.
For biological exploration, GO and enrichment analysis (perhaps the most user-friendly implementation of GSEA) are available. Use valuable public data (TCGA, GEO) to test your ideas, or generate/narrow new hypotheses, with an easy download and integration into your data analysis.
This tool suite empowers researchers to participate in their data analysis, exponentially shortening time to result and biological insight while improving accuracy of the findings.
We invite you to employ the cutting edge high-throughput techniques without the learning curve associated with advanced statistics, scripting languages and painful integration of different tools and formats!
Supported data types include any matrix data including RNAseq, microarrays, proteomics, miRNA, methDNA, Mulitplex and FC (genomic data support is coming soon). Case studies are available.
Qlucore started as a collaborative research project at Lund University (Sweden) between the Departments of Mathematics and Clinical Genetics.
Please contact Rolando Milian Rolando.firstname.lastname@example.org for questions or comments on this tool.