Gene expression

With Qlucore Omics Explorer you can examine and analyze data from gene expression experiments. Visualization is easy with strong support both for many types of plots such as heat maps and PCA plots.

Variable PCA plot

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.

Key functionality:

  • 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

Easy data import

Qlucore Omics Explorer supports many data file formats. Import can be done in several ways, with or without normalization. 

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Case Studies

RNA-seq case study

RNA-Seq analysis using Qlucore

Performing gene expression analysis based on RNA sequencing data, in Dilated Cardiomyopathy studies.

Stanford University, US

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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.

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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, UK

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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, China

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