scib.metrics.cell_cycle

scib.metrics.cell_cycle(adata_pre, adata_post, batch_key, embed=None, agg_func=<function mean>, organism='mouse', n_comps=50, verbose=False, recompute_cc=True, precompute_pcr_key=None)

Cell cycle conservation score

Compare the variance contribution of S-phase and G2/M-phase cell cycle scores before and after integration. Cell cycle scores are computed per batch on the unintegrated data set, eliminating the batch effect confounded by the batch_key variable.

\[CC \, conservation = 1 - \frac { |Var_{after} - Var_{before}| } {Var_{before}}\]

Variance contribution is obtained through principal component regression using pc_regression(). The score can be computed on full corrected feature spaces and latent embeddings.

Parameters

  • adata_pre – adata before integration

  • adata_post – adata after integration

  • embed – Name of embedding in adata_post.obsm. If embed=None, use the full expression matrix (adata.X), otherwise use the embedding provided in adata_post.obsm[embed]

  • agg_func – any function that takes a list of numbers and aggregates them into a single value. If agg_func=None, all results will be returned

  • organism – ‘mouse’ or ‘human’ for choosing cell cycle genes

  • recompute_cc – If True, force recompute cell cycle score, otherwise use precomputed scores if available as ‘S_score’ and ‘G2M_score’ in adata.obs

  • precompute_pcr_key – Key in adata_pre for precomputed PCR values for cell cycle scores. Ignores cell cycle scores in adata_pre if present.

Returns

A score between 1 and 0. The larger the score, the stronger the cell cycle variance is conserved.