scRNA-seq Analysis

Input data

This walkthrough uses a 10x Genomics filtered feature-barcode H5 file. CellPilot also supports a 10x MatrixMarket folder containing matrix, features or genes, and barcodes files.

curl -O https://cf.10xgenomics.com/samples/cell-exp/7.1.0/10k_mouse_kidney_scFFPE_singleplex_10k_mouse_kidney_scFFPE_singleplex/10k_mouse_kidney_scFFPE_singleplex_10k_mouse_kidney_scFFPE_singleplex_count_sample_filtered_feature_bc_matrix.h5

1. Load the dataset

1. Open CellPilot.
2. In the Data Type menu, choose scRNA-seq.
3. In the Data menu, choose Single sample.
4. Click Browse and select the downloaded H5 file.
5. Wait for CellPilot to load the matrix and start the analysis.

When the file is accepted, CellPilot reports the file format, cell count, gene count, and file path in the left data panel.

2. Let CellPilot run the default RNA pipeline

For scRNA-seq data, CellPilot runs the RNA workflow through bakana and scran.js. The default pipeline includes input parsing, RNA quality control, cell filtering, normalization, feature selection, PCA, neighbor graph construction, UMAP, graph clustering, clustering selection, and marker detection.

During processing, the chat/status area reports steps such as running quality control, PCA, UMAP, clustering, and marker detection. When analysis finishes, the UMAP view is colored by cluster.

3. Inspect the UMAP and clusters

1. Use the UMAP View to inspect cluster separation.
2. Click cluster labels in the legend to highlight selected clusters.
3. Use the chat panel to ask for a cluster summary or marker genes.

Tell me about cluster 6
Find markers for cluster 6
Find markers for PT

Marker results are shown as an analysis table. CellPilot returns positive marker genes for the requested cluster or renamed cluster label.

4. Plot marker genes

Use gene expression, violin, and dot plots to inspect kidney marker genes across clusters. Gene names can be entered in the chat command area.

Plot Slc5a2
Violin plot Slc5a2
Dotplot Slc5a2 Umod Nphs2 Pecam1 Ptprc
Change color to green black red

The color command changes the active gene or dot plot color scale, so use it after creating a feature plot or dot plot. Violin and dot plots use the active cluster assignments, including cluster labels that you renamed.

5. Rename clusters

After reviewing marker genes, rename clusters to biological labels. CellPilot keeps the original cluster IDs internally while displaying the new labels in the UMAP and downstream plots.

Rename cluster 1 to PT
Rename cluster 3 to TAL
Rename cluster 15 to Pod

6. Adjust analysis parameters

CellPilot supports common reanalysis commands from chat. Parameter updates rerun the necessary analysis steps and refresh the UMAP or clusters.

List parameters for cell filtering
Rerun the analysis by setting min gene = 500
Rerun umap with min dist = 0.4
Recluster the cells using resolution = 2.0

Cell filtering updates rerun the RNA workflow with the new QC thresholds. UMAP updates recompute the UMAP using the requested parameters. Clustering resolution updates recompute graph clustering and marker detection.

7. Save and revisit results

CellPilot saves analysis results for a loaded dataset when possible. If a previous CellPilot result is found the next time you load the same dataset, CellPilot can restore the saved UMAP and clusters while preparing normalized expression for gene plotting.