RNA-seq single cell analysis
Qlucore Omics Explorer supports a complete workflow for single cell RNA-seq data, where the UMAP plot is one of the components. Other useful functions are PCA and t-SNE 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, biotech, food and plant 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, t-SNE and UMAP to gain new insights.
Other important functionalities are:
- Direct import of 10x data (using Qlucore templates) including support for H5 data format.
- Automatic data filtering and optional data normalization.
- Variable pre-filtering to remove variables with few real measurement points across samples
- Subsampling to reduce the number of samples
- k-means++ clustering and ISOMAP
All of the above functionality can be used with any type of data and all existing functionalities can be used for single cell RNA-seq data.
Get tips and tricks on Single cell analysis.
Read more about RNA-seq analysis.
Single cell data analysis with Qlucore
Qlucore Omics Explorer includes a set of features directed specifically towards 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.
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