v2.8.0 Release

Introducing the Single Cell Integrated Analysis

Analyze two or more single cell experiments in a single guided analysis. Transform raw FASTQ files into a polished UMAP with cell type identities.  Explore insights and identify differences across groups and cell populations.  

Create and consolidate groups for comparative analysis 

Createing groups

  • Define the number of groups you would like to compare and the experiments to be included within each group
  • Launch the pipeline in the cloud and you will be emailed when your data is ready

Configure Quality Control Parameters

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  • Adjust Seurat Quality control parameters associated with each group in your analysis 
  • Specify additional cluster comparisons you would like to generate 

Get to your cell type identities faster

Conserved cell markers

  • Explore genes that are conserved across groups for each cluster for easier identification of cell types 

scRNA pathway enrichment

  • Explore gene set and pathway enrichment from databases such as KEGG ,EnrichR, and Reactome  

Analyze differences across cell populations and groups

scRNA expression plots

  • Curate cross group comparisons for differential expression analysis 
  • Search for a gene and visualize expression levels across all of your cell types and groups within  a UMAP or violin plot 
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  • Explore pathway enrichment and gene expression levels across all cell populations and groups. Customize and configure dynamic plots. 

Adjust Parameters and re-run steps 

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  • Adjust parameters and re-run steps as many times as you would like 

Transparent Methods & Analysis Summary 


  • Keep track of all parameters and methods used to generate your data 
  • consolidate and organize hundreds of plots and output files 
  • Seamlessly share results and collaborate with colleagues 

Ready to start your analysis? Learn how to use our integrated analysis here.