emdann

Checklist for saving and sharing scRNA-seq datasets

This is a checklist I use to harmonize scRNA-seq datasets before saving them as AnnData objects, loosely following cellxgene schema

Cleaning cell-level metadata

• Check for NAs or cells labelled as None - rename all cells with such label as 'unknown'
• Store main cell type annotation to use as adata.obs["cell_type"]
• Remove additional adata.obs columns containing alternative cell type annotation labels. If one or more alternative annotation labels need to be kept, rename to cell_type_* where * describes the difference with the main cell type annotation.
• Store disease annotation to adata.obs['disease'], labelling healthy cells as 'control' (not Control, healthy, normal)

emdann

library(miloR)

## Load dummy data
data(sim_trajectory)
milo.meta <- sim_trajectory$meta
milo.obj <- Milo(sim_trajectory$SCE)

## Build KNN graph neighbourhoods
milo.obj <- buildGraph(milo.obj, k=20, d=30)
milo.obj <- makeNhoods(milo.obj, k=20, d=30, refined=TRUE, prop=0.2, refinement_scheme="graph")

emdann

### A collection of frequently googled snippets ###

## Seaborn boxplot with groups and colors
sns.boxplot(data=data_df, x='x', y='y', hue='color_cov')

## Adding axes lines to plot
fig,ax = plt.subplots()
ax.axhline(y=0, color='r', linewidth=1, linestyle='--'); ## horizontal
ax.axvline(y=0, color='r', linewidth=1, linestyle='--'); ## vertical
plt.plot();