Successful visualisation. Examples from researchers

Use Qlucore Omics Explorer in all stages of your data analysis, from validation to visual reporting

A busy day in a scientist’s life includes many different tasks, data analysis being one of them. Qlucore Omics Explorer is designed to support you at all stages of your data analysis, from checking the quality of data in a pre-series to reporting final results with stunning visual plots.

At the heart of Qlucore Omics Explorer is the fast and generic calculation engine which generates plots and visualizations faster than any other tool. This enables you to secure full interactivity and make your analysis fast, easy and productive. The fact that the engine is generic allows you to work with many types of data, some examples include: flow cytometry, proteomics, DNA methylation, RNA-seq, array.

You can work not only with your own data but also with the data of others, either through downloading directly from sources as Gene Expression Omnibus (GEO) or by using the Wizard and importing data sets from co-workers.

Here are two examples of how Qlucore Omics Explorer is currently helping scientists in their research and also enables improved resource use by freeing up time from bioinformaticians:

Stanford University is using induced Pluripotent Stem Cells (iPSCs) to study molecular mechanisms in Dilated Cardiomyopathy. They used RNA-seq data.

"We have a high volume of experiments and we want results promptly. Qlucore software is definitely helping," says Dr Matsa at Stanford University.'It means that cell biologists like myself can look at data, analyze and perform statistical analyses for a presentation or a paper without having to go through our bioinformatician'.

At Beijing Normal University a group is working with classification of glioma using, among other, gene expression data. To come up with the classification, the researchers studied two gene co-expression modules around key signaling pathways that are conserved between neural development and the formation of gliomas. In the search for patterns, they use publicly available datasets from three continents, including gene expression data, genomic data and clinical data. To analyze these datasets and look for links, Qlucore Omics Explorer is used and the results are published in PNAS.

Both institutions share their experiences with Qlucore Omics Explorer in these downloadable case studies.

Learn more about the general functionality by watching these 
video tutorials.