End-to-end package for single cell transcriptome analysis

Transform raw in-house data to insights

Not just creating a gateway to published works, BioTuring Browser is an end-to-end solution for YOUR own single-cell RNA sequencing data.

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Quantification

Quantify transcripts at unparalleled speed using Hera-T. No commands are required.

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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 protein information.

Study cell fate decisions with single cell trajectory analysis

Build the trajectory graph from your single-cell data, order single cells in pseudotime, and explore differentially expressed genes along any selected branch.

Get scalable
3D visualization
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.

Bioturing scRNA-seq software greatly accelerates and enables our research, through easy to use intuitive analytics, visualization and extensive database of curated and pre-processed experiments

Eugene Bolotin - Senior Bioinformatics Scientist, Kite Pharma

The BioTuring Browser is a game changer in the Immune Oncology field to speed up single cell data sharing among biologists, immunologists and bioinformaticians. Empowering collaboration in annotating cells, discovering unknown cell populations, cell states or cell interactions is crucial to draw the best picture ever of the highly heterogenous tumor microenvironment. Users have access to a growing public as well as their private knowledge base, which makes the BioTuring platform a swiss-army-knife for better understanding cells at the single cell level.

Molecular Oncology and Immunology Lab, IFOM

BBrowser allows biologists to handle scRNA-seq data without programming knowledge. Intuitive operation. Functions are updated. Public data can be imported. It is very helpful.

Researcher (Pharmacology), Chugai Pharmaceutical

I came across BBrowser while going through the Bioturing website and have been very impressed by the ease of use, capacity and capability of this unique platform. Within minutes from starting to use this tool, I was able to download single-cell sequencing datasets with metadata, obtain visualizations and biostatistical analyses including correlation and hierarchical clustering, analyse data by age, sex and pathology and carry differential gene expression analyses for my genes of interest. Overall, an amazing tool to have for every researcher engaged in scRNA approaches. Kudos to the developers for bringing this amazing platform to academics engaged in single-cell research. Looking forward to the addition of more studies/workflows and features to this already exciting software!

Anand Hardikar, Western Sydney University, Sydney Australia

The Bioturing Browser with single cell add-on provides one of the simplest interfaces for quickly moving from raw data to cluster analyses with minimal experience. The built-in HeraT alignment processes are remarkably quick and less computationally intensive than other scRNA-seq offerings.

Chris Ahuja - University of Toronto.

Bioturing Browser is an intuitive and powerful software for exploration and visualization of scRNA-Seq data. Its fast and easy access to the vast amounts of curated datasets is very helpful for our drug discovery research.

Niv Sabath - Senior Scientist, Compugen

Publications

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