While single-cell RNA sequencing is a fast-growing technology and helping to resolve tissue heterogeneity and cellular transitional states at high resolution, not all the scientists can explore their data by themselves due to the large data size, on matrices with thousands of cells times thousands of genes, as well as due to the complexity in data analysis. So far, there is no standard pipeline for the analysis and every time, the bioinformaticians need to communicate with wet-lab scientists back and forth to understand the experiment setups and alter data processing steps to fully extract the meaningful biological information from the data.
One approach to the issue is to develop GUI platforms for wet-lab scientists to interact with their data, perform exploratory analyses or create their annotation of cell clusters by themselves. However, those platforms lack the flexibility of the command line to customize the analysis pipeline for each dataset.
To foster collaboration in single-cell data analysis, BioTuring has adapted its single-cell analytics platform to import processed data from popular single-cell analysis packages like Seurat (Butler et. al 2018) and Scanpy (Wolf et. al 2018). The software, BioTuring Browser or BBrowser, takes in Seurat and Scanpy objects (.rds and .h5ad/.h5 formats) for visualizations and brings along various downstream analytical options in an interactive UI. For data processed by other packages, one can convert it to .rds or .h5ad/.h5 using available conversion tools and import to the software.
By taking in the single-cell objects, BBrowser helps bioinformaticians effectively hand over the data to wet-lab collaborators, together with quality control, batch correction, principal component analysis (PCA) results, t-SNE or UMAP coordinates, and clustering information. On the software, biologists can find marker genes and enrichment processes, characterize cell subsets, run differential expression analysis, comparing gene expression and cell compositions in different conditions and many more, all in an intuitive and flexible approach.
Besides, BBrowser also facilitates data management and sharing among groups of scientists via a private data repository set up in the institution’s shared network. Users with access to that folder can upload and download data, including additional annotations and analyses performed. The software can also create customized metadata for the library, making available experiment setups, questions, and comments for each dataset and boosting the communication in a large group setting.
To support academic research, importing Seurat and Scanpy objects and sharing data through the institutional networks on BBrowser is now FREE for academic users.
In addition to Seurat and Scanpy objects, BBrowser also supports importing FASTQ and gene expression matrices (.MTX/.TSV/.CSV formats). With a 5.5 million cell database built-in the software, users of BBrowser can download the latest scRNA-seq datasets from publications in a processed, ready-to-analyze format, for the reproduction of the valuable published works and compare their current data to those by a transcription profile search engine.
Availability – BioTuring Single-cell Browser can be downloaded at https://bioturing.com/product/bbrowser.