Qlucore Omics Explorer

Qlucore Omics Explorer is developed to allow the workflow which best suits you and your experiments and maximizes the outcome of your research.

For RNA-seq data is it possible to analyze expression levels in a synchronized model with filtering along the genome.

You decide the workflow

Visualize

Visualization is key.

By combining instant visualization with powerful statistics and flexible selection methods, you will be able to see your results immediately.

Qlucore Omics Explorer supports 10 different plot types and with the NGS module is a Genome browser included.

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Explore

Instant exploration is one of the key features.

As a user, you decide your own workflow and starting point. You are in control and can tailor the exploration to meet your specific needs.

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Analyze

The combination of powerful statistics and instant visualization can generate exciting results.

One of the cornerstones is the possibility to analyze data using a flexible and easy to use general linear statistical model. You can also add methods through the Open API to R. With the NGS module filtering on genomic entities such as read coverage and variants are supported. More options are supported through the GSEA workbench, the kmeans++ clustering and the generation and use of classifiers.

More about Analysis >

Share

You can share your results in a number of different ways.

The unique global log and restore function not only lets you keep track of what you have done, but also allows you to store information of each analysis step you have performed.

More about Sharing >

Easy data import

A wide selection of file formats and data types are supported. 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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Analysis of proteomics data using Qlucore

Using proteomics to understand cardiovascular disease

The Center for Interdisciplinary Cardiovascular Sciences, Boston, US

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Analyzing proteomics and transcriptomics data

Study of hundreds of entries about pollutants and nutrients in different fish species, showing how levels are changing over time.

National Institute of Nutrition and Seafood Research (NIFES), Norway

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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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