Welcome to BestopCloud!
Data processing
Seurat standard workflow: quality control, normalization, feature selection, dimensionality reduction and cluster.
Data integration
Harmony, an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions.
Data viewer
Cell expression and metadata information will be displayed on the UMAP.
Cell type annotation - SingleR
SingleR assigns cellular identity for single cell transcriptomes by comparison to reference datasets of pure cell types.
Cell type annotation - ScType
Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data.
Differential expression analysis
The scRNA-seq data can be tested for genes that are differentially expressed to identify marker genes or genes that are upregulated or downregulated in specific conditions.
Enrichment analysis
Gene Set Enrichment Analysis is a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states(e.g. phenotypes).
Cell–cell communication - CellChat
CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from scRNA-seq data.
Copy number analysis - CopyKat
CopyKAT: Inference of genomic copy number and subclonal structure of human tumors from high-throughput single cell RNAseq data
Data upload & settings
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Data upload & settings
Data upload & settings
UMAP plots to show the overall distribution of the data for selected variables (e.g., samples, clusters, cell types).
A stacked barplot to show the proportion of
variable X (e.g., cell types) in variable Y (e.g., samples).
Subset settings:
Data input & settings
Data input & settings
Data upload & settings
Group settings:
Analysis settings: