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A next-generation platform for single-cellmulti-omics data
Meet BioTuring Browser and its new CITE-seq dashboard, a complete package for interactively exploring single-cell gene expression data in parallel with surface protein information
Access 12489516 cellsfrom published works
A new way to reviewpublished data
Instantly access and reanalyze latest single-cell RNA-seq and CITE-seq datasets from publications, all uniformly annotated, and ready for visualization.
Transform raw
in-house data
to insights
Not just creating a gateway to published works, BioTuring Single-cell Browser is an end-to-end solution for YOUR own single-cell RNA sequencing data.
Quantification
Quantify transcripts at unparalleled speed using Hera-T. No commands are required.
Batch effect removal
Retain true biological variances with various batch effect removal methods:
• CCA
• MNN
• Harmony
Dimension reduction and clustering
• Perform dimension reduction with t-SNE and UMAP
• Cluster the cells by k-means and graph-based clustering
• Explore novel cell sub-types on an interactive sub-clustering dashboard
Annotation and prediction
• Predict cell types in real time upon selecting any groups of cells. The knowledge base for prediction can be customized to your own definition.
• Explore marker genes and run enrichment analysis
Comparison
• Track the compositional changes in different treatments, or which treatment enriches different cell types.
• Find differentially expressed genes in any two groups of cells such as two cell types, sub-types, conditions, or any two stages of the disease
Harness
the synergy of
single-cell
multi-omics
Perform parallel analysis combining single-cell RNA-seq data, TCR-seq data and cell surface information
CITE-Seq data analysis:
- t-SNE based on protein information
- Query protein expression across all cells
- Feature plot
Pairing clonotype information:
- Explore clonotype abundances
- View antigen information
- Find differentially expressed genes between 2 clonotypes
Get scalable
3D visualizations
on a laptop
BioTuring Single-cell Browser is optimized to visualize up to 1.3 million single cells at a time on a standard laptop with interactive t-SNE and UMAP.
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Publications
