Making RNA-seq single cell analysis easier

Qlucore Omics Explorer supports a complete workflow for single cell RNA-seq data, where the t-SNE plot is one of the components. Other useful functions are PCA plots, k-means++ clustering and subsampling as well as variable pre-filtering.

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.



Single cell RNA-seq is a technique that is becoming more widely used. The amount of data generated from these experiments tends to be large, and data sets with more than a thousand samples are commonplace. Large data sets and fast analysis are exactly what Qlucore Omics Explorer is designed for. Using an ordinary PC/laptop you can work with these extremely large data sets and use visualizations such as PCA and t-SNE to gain new insights. Other important functionality is:

  • Variable pre-filtering to remove variables with few real measurement points over the samples
  • Subsampling to reduce the number of samples if required
  • A new pre-filter module with extensive options to remove unwanted variables
  • k-means++ clustering and ISOMAP

All of the above functionality can be used with any type of data and all existing functionality can be used for single cell RNA-seq data.

Get some tips and tricks on Single cell analysis.

Read more about RNA-seq analysis here.


Single cell data analysis with Qlucore

In this webinar we introduce the functionality added in version 3.4 that is especially useful for single cell RNA-seq analysis


Does it work on my data?

Answer the four quick questions below and find out if you can use Qlucore on your data. 

For more details about supported data formats and data import see Data Import or Contact us with questions.

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

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, UK

Read more

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

Read more

Interpreting Leukemia proteomics with Qlucore

In this case study Qlucore Omics Explorer is used to generate new ideas and hypotheses through exploration and analysis of proteomics data.

UT MD Anderson Cancer Center in Houston, Texas, US

Read more

Get started now with a free 10 days trial of Qlucore Omics Explorer!

Start here