{
"papers": [
{
"n": 1679,
"doi": "10.1038/nn.4216",
"value": "49",
"method": "single-cell RNA-seq (SMART-seq)",
"metric": "n_transcriptomic_types_V1",
"n_analyzed": "1679",
"ci_or_error": "",
"text_access": "abstract_only",
"n_definition": "single cells profiled by SMART-seq",
"scope_region": "single cortical area (VISp)",
"study_system": "adult mouse primary visual cortex (V1)",
"taxonomic_level": "fine type (t-type)",
"scope_population": "all transcriptomically profiled cortical cells",
"value_source_sentence": "We identified 49 transcriptomic cell types, including 23 GABAergic, 19 glutamatergic and 7 non-neuronal types.",
"experimental_conditions": "Cre-line targeted FACS-sorted cells, SMART-seq"
},
{
"n": 23822,
"doi": "10.1038/s41586-018-0654-5",
"value": "133",
"method": "single-cell RNA-seq (SMART-seq)",
"metric": "n_transcriptomic_types_VISp_ALM",
"n_analyzed": "23822",
"ci_or_error": "",
"text_access": "abstract_only",
"n_definition": "single cells profiled by SMART-seq",
"scope_region": "two cortical areas",
"study_system": "adult mouse primary visual cortex (VISp) and anterior lateral motor cortex (ALM)",
"taxonomic_level": "fine type (t-type)",
"scope_population": "transcriptomically profiled cortical neurons",
"value_source_sentence": "We define 133 transcriptomic cell types by deep, single-cell RNA sequencing.",
"experimental_conditions": "Cre-line targeted FACS-sorted cells, SMART-seq"
},
{
"n": 1300000,
"doi": "10.1016/j.cell.2021.04.021",
"value": "~1,300,000",
"method": "single-cell RNA-seq (10x)",
"metric": "n_cells_profiled_isocortex_HPF",
"n_analyzed": "1300000",
"ci_or_error": "",
"text_access": "abstract_only",
"n_definition": "single cells profiled by scRNA-seq",
"scope_region": "whole isocortex + hippocampal formation",
"study_system": "adult mouse isocortex and hippocampal formation",
"taxonomic_level": "fine type (t-type)",
"scope_population": "all dissociated cells",
"value_source_sentence": "We profiled ~1.3 million cells covering the entire adult mouse isocortex and HPF and derived a transcriptomic cell-type taxonomy revealing a comprehensive repertoire of glutamatergic and GABAergic neuron types.",
"experimental_conditions": "whole isocortex+HPF dissociation, 10x scRNA-seq"
},
{
"n": 4000000,
"doi": "10.1038/s41586-023-06812-z",
"value": "5322",
"method": "scRNA-seq + MERFISH",
"metric": "n_clusters_whole_brain_atlas",
"n_analyzed": "4000000",
"ci_or_error": "",
"text_access": "abstract_only",
"n_definition": "single cells profiled by scRNA-seq post-QC",
"scope_region": "whole mouse brain",
"study_system": "adult mouse whole brain",
"taxonomic_level": "cluster",
"scope_population": "all dissociated cells",
"value_source_sentence": "The atlas is hierarchically organized into 4 nested levels of classification: 34 classes, 338 subclasses, 1,201 supertypes and 5,322 clusters.",
"experimental_conditions": "10x scRNA-seq + MERFISH spatial transcriptomics"
}
],
"audit_issues": [
{
"dimension": "scope_region",
"description": "Rows span V1 only → VISp+ALM → whole isocortex+HPF → whole brain. With expanding brain coverage, cluster counts mechanically increase from added regions, not from finer resolution within a fixed scope. This is the canonical scope-mismatch trap.",
"entries_affected": [
"10.1038/nn.4216",
"10.1038/s41586-018-0654-5",
"10.1016/j.cell.2021.04.021",
"10.1038/s41586-023-06812-z"
]
},
{
"dimension": "metric_definition",
"description": "Row 3 reports n_cells_profiled (~1,300,000) — a sample-size measure — while rows 1, 2, 4 report n_transcriptomic_types (49, 133, 5,322). These are different quantities on different scales (cells vs. types) and cannot share a y-axis.",
"entries_affected": [
"10.1016/j.cell.2021.04.021"
]
},
{
"dimension": "taxonomic_level",
"description": "Rows mix t-types (rows 1–2) with hierarchically-organised 'clusters' (row 4, finest level of a 4-level taxonomy: 34 classes / 338 subclasses / 1,201 supertypes / 5,322 clusters). 5,322 clusters and 49 t-types are not at the same taxonomic grain.",
"entries_affected": [
"10.1038/nn.4216",
"10.1038/s41586-018-0654-5",
"10.1038/s41586-023-06812-z"
]
}
],
"audit_verdict": "REDESIGN",
"comparison_id": "transcriptomic-cell-types-mouse-cortex",
"comparison_name": "Number of transcriptomic cell types defined in successive mouse cortex single-cell taxonomies",
"comparison_type": "timeline",
"what_it_reveals": "Successive Allen taxonomy releases redefine 'transcriptomic cell type' at increasingly fine granularity, making cell-type-specific connectivity rules a moving target.",
"homogeneity_check": {
"caveats": [
"Each study expands geographic coverage (V1 → VISp+ALM → isocortex+HPF → whole brain), so cluster counts are not directly comparable.",
"Taxonomic granularity differs (t-types vs 'supertypes' vs 'clusters')."
],
"n_definition_uniform": "true",
"scope_region_uniform": "false",
"taxonomic_level_uniform": "false",
"scope_population_uniform": "true"
},
"suggested_plot_type": "timeline",
"mandatory_caption_caveats": [
"Brain coverage expands from V1 → 2 cortical areas → isocortex+HPF → whole brain across rows; cluster counts are not directly comparable as a 'discovery progression' because they reflect added tissue, not finer resolution.",
"Taxonomic grain differs: rows 1–2 report t-types; row 4 reports 'clusters' at the finest of four nested levels (whole-brain atlas also has 34 classes / 338 subclasses / 1,201 supertypes that are closer in grain to the earlier t-type counts).",
"Phase 7 writer: REDESIGN verdict — implement as: Restrict to a single scope (e.g., mouse cortex) and report taxonomic counts at the equivalent level across studies. For the whole-brain atlas (Yao 2023), use the subclass/supertype count rather than the cluster count if comparing to earlier t-type-level papers. Correct the row-3 metric: replace n_ce"
]
}