With Qlucore Omics Explorer you can examine and analyze data from gene expression experiments. Easy visualization is built into the tool and configuration is easy and fast for many different plots such as heat maps (heatmap) and PCA plots.
Qlucore Omics Explorer is a D.I.Y next-generation bioinformatics software for research in life science, plant- and biotech industries, as well as academia. The powerful visualization-based data analysis tool with inbuilt powerful statistics delivers immediate results and provides instant exploration and visualization of big data.
GENE EXPRESSION ANALYSIS MADE EASY
With a few mouse clicks the discriminating genes are identified and results are available in publication ready lists and plots.
Data can be generated either by microarrays or through RNA-seq techniques. Direct import and normalization is available for Affymetrix, Agilent and aligned BAM files coming from any NGS platform.
RNA-seq data can be analyzed with Qlucore Omics Explorer base module. If you add the NGS module many more options open up - it will for instance be possible to analyze data in a synchronized model both doing statistical filtering on expression levels and filter on genomic entities. All this can be done with synchronized plots such as a Genome browser and a heatmap or PCA plot.
- Identify discriminating genes with a few mouse clicks
- Show results in the flexible and easy-to-use heat map with hierarchical clustering
- Verify your hypotheses using powerful statistics including ANOVA and different forms of regressions
- Expand the analysis using the integrated GO Browser
- Compare with pathways and other biological information using the integrated and user friendly Gene Set Enrichment analysis (GSEA) Workbench
- Explore new ideas focusing on gene and sample subsets with Dynamic PCA
- Heat maps, box plots, bar plots, line plots, PCA plots and more, both in 2D and 3D
RNA-Seq analysis using Qlucore
Performing gene expression analysis based on RNA sequencing data, in Dilated Cardiomyopathy studies.
Stanford University, USRead more
Using Qlucore in epigenetics research studies
A range of samples including DNA from patient blood, primary tissue from tumors, and cell lines, are studied.
Cancer Genetics Program at the Hospital for Sick Children (SickKids) in Toronto, Canada.Read more
Qlucore analysis of transcriptomic data
The study includes working with data from more than 400 arrays. Visualization is used in the effort to understand the human growth process.
University of Manchester, UKRead more
Analysis of public data using Qlucore
This case study is an example of how the use of public information from multiple sources was used to propose a new classification for glioma cancer.
Beijing Normal University, ChinaRead more