Single Cell Analysis for Everyone
Empowering researchers and clinicians to gain insights from single cell experiments with interactive data visualization and easy to use but powerful machine learning methods to classify and model single cell data.
Jul 28, 2019
Identify the genes affiliated with osteoarthritis progression in the cartilage data gathered by Ji Q et al. (Annals of the Rheumatic Diseases, 2019) Read more >
Jun 14, 2019
We project single cell data from an AML patient undergoing chemotherapy onto a t-SNE of a healthy individual to analyse cell population changes in the course of treatment. Read more >
Jun 6, 2019
Identify cell populations in healthy human bone marrow and take a look at the putative cell differentiation trajectories. Read more >
Load data from any platform and filter outlier cells. Normalize expression values across samples and platforms. Identify and explore sub-populations with a sample and across multiple samples.
Identify signature genes for each subpopulation using multiple methods. Use gene ontology enrichment to explore the biological meaning and identify cell types.
Build classifiers to identify the cell type of each subpopulation. Use classifier on new data samples to predict cell types and focus on interesting cell type populations.