Workflow and Report page overview

The analysis starts with the Seurat object for each sample produced by our single-cell RNA-seq analysis pipeline. After combining and integrating these R objects, filtering, normalization, dimension-reduction using PCA, and clustering at resolutions from 0.1-2.0 are performed, along with UMAP and t-SNE plot generation and identification of marker genes for each cluster and differentially expressed genes between conditions for each cluster. Summary statistics and plots are displayed for a quick assessment of data quality. Interactive UMAP, t-SNE, and PCA plots allow for real-time data exploration at both the cluster- and gene-level along with a summary table and heatmap of marker gene expression levels.


Under the "Report" tab, a series of interactive and downloadable plots allow for in-depth data exploration


-summary statistics at the cell- and gene/feature- level both before and after filtering


-cell projections in 2D space resulting from t-SNE, UMAP, and PCA algorithms at different resolutions. This allows for in-depth exploration of the number of preferred clusters along with gene expression levels within those clusters
-also included is a summary violin + dot-plot showing the distribution of gene expression levels per cluster at the chosen gene and resolution

Cluster table

-The "Cluster gene markers" table contains marker genes for each cluster at the chosen resolution, identified using differential gene expression analysis comparing each cell cluster to all others. The "Conserved gene markers" table contains differentially expressed genes of each cluster whose expression is conserved between biological groups. The "Differential between conditions" table provides a list of genes for each cluster that are differentially expressed between the biological groups.


-heatmap of marker genes identified using differential gene expression analysis for each cluster

Output Files

Under the "Info" tab, intermediate files produced by the pipeline are available for viewing or download:

-gene-by-cell count matrix in comma-separated formatseurat/jackstraw.overall.pvalues.csv

-table of the statistical significance of genes in each principle component

-table of seurat object metadata for each cell after filtering, normalization, and clustering

-resulting principle component data in a comma-separated table

-seurat R data object containing raw and normalized data, and metadata

-table of cell coordinates in t-SNE space\

-table of cell coordinates in UMAP space

-results of marker gene identification and heatmaps at resolutions from 0.1-2.0