BBrowser: Making single-cell data easily accessible

BioTuring’s BBrowser is a software solution that helps scientists effectively analyze single-cell omics data. It combines big data with big computation and modern data visualization to create a unique platform where scientists can interact and obtain important biological insights from the massive amounts of single-cell data. BBrowser has three main components: a curated single-cell database, a big-data analytics layer, and a data visualization module. BBrowser is available for download at: https://bioturing.com/bbrowser/download.

[1]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Nayoung K. D. Kim,et al.  Single-cell RNA sequencing demonstrates the molecular and cellular reprogramming of metastatic lung adenocarcinoma , 2020, Nature Communications.

[3]  Leland McInnes,et al.  UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction , 2018, ArXiv.

[4]  Son K. Pham,et al.  Venice: A New Algorithm for Finding Marker Genes in Single-Cell Transcriptomic Data , 2020, bioRxiv.

[5]  Gang Feng,et al.  Disease Ontology: a backbone for disease semantic integration , 2011, Nucleic Acids Res..

[6]  Aviv Regev,et al.  Cumulus provides cloud-based data analysis for large-scale single-cell and single-nucleus RNA-seq , 2020, Nature Methods.

[7]  Fan Zhang,et al.  Fast, sensitive, and accurate integration of single cell data with Harmony , 2018, bioRxiv.

[8]  P. Jaccard Distribution de la flore alpine dans le bassin des Dranses et dans quelques régions voisines , 1901 .

[9]  Samuel F. Bakhoum,et al.  Regenerative lineages and immune-mediated pruning in lung cancer metastasis , 2019, Nature Medicine.

[10]  Ruhong Zhou,et al.  A Public BCR Present in a Unique Dual-Receptor-Expressing Lymphocyte from Type 1 Diabetes Patients Encodes a Potent T Cell Autoantigen , 2019, Cell.

[11]  Fabian J Theis,et al.  SCANPY: large-scale single-cell gene expression data analysis , 2018, Genome Biology.

[12]  S. Jennrich,et al.  CXCR4 Is Dispensable for T Cell Egress from Chronically Inflamed Skin via the Afferent Lymph , 2014, PloS one.

[13]  Yue Liu,et al.  CLO: The cell line ontology , 2014, Journal of Biomedical Semantics.

[14]  Justine Jia Wen Seow,et al.  Onco-fetal Reprogramming of Endothelial Cells Drives Immunosuppressive Macrophages in Hepatocellular Carcinoma , 2020, Cell.

[15]  Lincoln Stein,et al.  Reactome: a database of reactions, pathways and biological processes , 2010, Nucleic Acids Res..

[16]  C E Lipscomb,et al.  Medical Subject Headings (MeSH). , 2000, Bulletin of the Medical Library Association.

[17]  Gene Ontology Consortium The Gene Ontology (GO) database and informatics resource , 2003 .

[18]  Andrew K. Sewell,et al.  VDJdb: a curated database of T-cell receptor sequences with known antigen specificity , 2017, Nucleic Acids Res..

[19]  Laleh Haghverdi,et al.  Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors , 2018, Nature Biotechnology.

[20]  Ambrose J. Carr,et al.  Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment , 2018, Cell.

[21]  Son K. Pham,et al.  Hera-T: an efficient and accurate approach for quantifying gene abundances from 10X-Chromium data with high rates of non-exonic reads , 2019, bioRxiv.

[22]  Bertrand Z. Yeung,et al.  Cell Hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics , 2018, Genome Biology.

[23]  Vanessa M. Peterson,et al.  Multiplexed quantification of proteins and transcripts in single cells , 2017, Nature Biotechnology.

[24]  Christoph Hafemeister,et al.  Comprehensive integration of single cell data , 2018, bioRxiv.

[25]  M. Tosolini,et al.  Single-Cell Signature Explorer for comprehensive visualization of single cell signatures across scRNA-seq data sets , 2019, bioRxiv.

[26]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .