emdann

Continuous covariate

# Fit model
pds2_model = pertpy.tl.PyDESeq2(adata, design='~ my_cont_covariate + other_covariates')

# Get contrast
cont_contrast = pd.Series(0, index=pds2_model.design.columns)
cont_contrast.loc['my_cont_covariate'] = 1

emdann

import yaml
import pandas as pd
from typing import Dict, Any

def flatten_list_values(value: Any) -> str:
    """Convert list values to comma-separated strings."""
    if isinstance(value, list):
        return ', '.join(str(item) for item in value)
    return str(value) if value is not None else ''

emdann

Make an AnnData from a Seurat object

Extract key components in R

library(Seurat)
library(Matrix)

rds_file <- '/path/to/seurat.rds'
dataset_suffix <- sub("\\.rds$", "", rds_file)
data <- readRDS(rds_file)

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();