BioTuring
Single-cell Browser

A modern platform for single-cell sequencing data analysis

Access 5266097 cellsfrom published works

A new way to reviewpublished data

Instantly access and reanalyze single-cell RNA sequencing datasets from latest high-impact publications (5,266,097), preprocessed and uniformly annotated.

A unique microglia type associated with restricting development of Alzheimer’s disease (Keren-Shaul et al., 2017)

Finding differentially expressed genes

The single-cell transcriptional landscape of mammalian organogenesis (Cao et al., 2019)

3D UMAP

Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris (Tabula Muris Consortium, 2017)

Identifying cell types with real-time prediction

Single-Cell RNA-Seq Reveals AML Hierarchies Relevant to Disease Progression and Immunity (van Galen et al., 2019)

Finding marker genes

Single-cell map of diverse immune phenotypes in the breast tumor microenvironment (Azizi et al., 2018)

Pairing clonotype data with expression data

Dysfunctional CD8 T Cells Form a Proliferative, Dynamically Regulated Compartment within Human Melanoma (Li et al., 2019)

Viewing composition of a cell population

The bone marrow microenvironment at single-cell resolution (Tikhonova et al., 2019)

Querying gene expression

Clark, Brian S., et al. "Single-Cell RNA-Seq Analysis of Retinal Development Identifies NFI Factors as Regulating Mitotic Exit and Late-Born Cell Specification (Clark et al., 2019)

UMAP for tracking retinal development

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

Pairing V(D)J data

With BioTuring Single Cell Browser, you can pair TCR repertoire sequencing data with single cell RNA-seq expression data, at the same time get more information on the epitope that can be recognized

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.

Get started with

BioTuring Single Cell Browser