marker_genes_dict#

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marker_genes_dict(data: AnnData, groups: Sequence[str] | None = None, *, key: str = 'rank_genes_groups', n_genes: int = 5) → dict[str, list[str]]#

Select the top-ranked marker gene names per group from a precomputed ranking.

Like marker_genes, but keeps the grouping: each group maps to its own full top-n_genes list.

Parameters:

  • data (AnnData) – The single-cell data object holding the precomputed differential expression ranking.

  • groups (Sequence[str] | None, default None) – Subset of groups to pull markers from, in order. None keeps all groups in their stored order.

  • key (str, default 'rank_genes_groups') – The key under which the precomputed ranking is stored on data.

  • n_genes (int, default 5) – Number of top genes to pull per group.

Returns:

dict[str, list[str]] – Mapping from group label to its top-n_genes gene names, in group order. Each list is complete; a gene that ranks highly in several groups appears under each of them.

Raises:

  • UnsupportedDataTypeError – If data is not a supported single-cell data object.

  • KeyNotFoundError – If the ranking result or a requested group is missing.

  • ValueError – If n_genes is out of range.

  • TypeError – If groups is neither a Sequence of strings nor None.

Notes

Reads only the gene names, not their scores; use markers to plot the ranking itself. Use marker_genes for a flat, de-duplicated list.

Examples

Inspect the top markers of each group.

import scanpy as sc

import cellestial as cl

data = sc.datasets.pbmc68k_reduced()

cl.marker_genes_dict(data, n_genes=3)

{'CD4+/CD25 T Reg': ['RGS19', 'HIST1H4C', 'IL32'],
 'CD4+/CD45RA+/CD25- Naive T': ['ITM2A', 'RPL39', 'TIMM10'],
 'CD4+/CD45RO+ Memory': ['CAPG', 'GABARAPL2', 'FDX1'],
 'CD8+ Cytotoxic T': ['CCL5', 'GNLY', 'NKG7'],
 'CD8+/CD45RA+ Naive Cytotoxic': ['CD8B', 'CD8A', 'RP11-291B21.2'],
 'CD14+ Monocyte': ['C1QA', 'PSAP', 'COX14'],
 'CD19+ B': ['CD79A', 'CD79B', 'MS4A1'],
 'CD34+': ['PRSS57', 'SNHG7', 'SERPINB1'],
 'CD56+ NK': ['GNLY', 'NKG7', 'CD7'],
 'Dendritic': ['CST3', 'LYZ', 'LST1']}
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