Version Compatibility

Reference examples tested with: DESeq2 1.42+, pandas 2.2+, scanpy 1.10+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• R: packageVersion('<pkg>') then ?function_name to verify parameters

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Marker Genes and Cell Type Annotation

Find differentially expressed genes between clusters and annotate cell types.

Scanpy (Python)

Goal: Identify cluster-specific marker genes, score gene sets, and annotate cell types using Scanpy.

Approach: Perform differential expression testing between clusters with Wilcoxon rank-sum, visualize markers with dot plots and heatmaps, and assign cell type labels manually.

"Find marker genes for each cluster" → Test each cluster against all others for differentially expressed genes and rank by statistical significance and fold change.

Required Imports

import scanpy as sc
import pandas as pd

Find Markers for All Clusters

# Find marker genes for each cluster vs all others
sc.tl.rank_genes_groups(adata, groupby='leiden', method='wilcoxon')

# View top markers
sc.pl.rank_genes_groups(adata, n_genes=10, sharey=False)

# Get results as DataFrame
markers = sc.get.rank_genes_groups_df(adata, group=None)
print(markers.head(20))

Marker Detection Methods

# Wilcoxon rank-sum test (default, recommended)
sc.tl.rank_genes_groups(adata, groupby='leiden', method='wilcoxon')

# t-test
sc.tl.rank_genes_groups(adata, groupby='leiden', method='t-test')

# Logistic regression
sc.tl.rank_genes_groups(adata, groupby='leiden', method='logreg')