Visualization
The vis
workflow can take a MuData
object from any of the other Panpipes
workflows and visualize the following (where applicable):
for custom markers:
heatmaps
dotplots
embeddings such as PCA and UMAP coloured by the marker expression
for categorical variables:
barplots, e.g the number of cells per sample ID
stacked barplots, e.g. the number of cells in each cluster split by sample ID
embeddings such as PCA and UMAP coloured by the categorical variable
for continuous variables:
violin plots split by categorical variables, e.g doublet score per disease group
embeddings such as PCA and UMAP coloured by the continuous variable
for paired markers or metrics:
scatter plots, e.g. scatter plot of
total_counts
on the x axis andn_genes_by_counts
on the y axis
For plots with custom markers follow the guidelines in Gene list formats to create the input gene lists.
Steps to run
Activate conda environment
conda activate pipeline_env
Generate the config and log files with
panpipes vis config
and edit the pipeline.yml file(Optional) Prepare gene list files, more details here
Run complete workflow with
panpipes vis make full --local
The Visualization tutorial guides you through the visualization step by step.
Expected structure of MuData object
The vis
workflow can take the MuData outputs from any of the other Panpipes
workflows, but make sure not to ask the pipeline to produce visualisations using data that has not been computed, e.g. plotting UMAPs using a MuData object which does not contain anything in the X_umap slot.