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.
MAKING RNA-SEQ SINGLE CELL ANALYSIS EASIER
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
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