Version history

{
  "kind": "infographic",
  "prompt": "PV interneuron subtype resolution varies dramatically by method and brain region. Visual cortex Patch-seq identifies 7 Pvalb met-types. Isocortex-wide scRNA-seq resolves 3 supertypes. Hippocampal scRNA-seq with morphological identification finds continuous variation without discrete types. This reveals a tension between discrete classification and continuous variation.",
  "provider": "other",
  "raw_fields": {
    "papers": [
      {
        "n": 517,
        "doi": "10.1016/j.cell.2020.09.057",
        "value": "7",
        "method": "Patch-seq",
        "metric": "Number of Pvalb met-types identified",
        "n_analyzed": "517 with morphology",
        "ci_or_error": null,
        "text_access": "fulltext",
        "n_definition": "neurons with full morphological reconstruction",
        "scope_region": "visual cortex",
        "study_system": "mouse visual cortex",
        "taxonomic_level": "met-type (multimodal integration)",
        "scope_population": "Pvalb subclass only",
        "value_source_sentence": "the Pvalb subclass had t-types that predominantly targeted L2/3 (Pvalb Tpbg), L2/3 and L4 (Pvalb Reln Itm2a), and L5 and L6 (Pvalb Sema3e Kank4, Pvalb Gabrg1).",
        "experimental_conditions": "Patch-seq with morphological reconstruction"
      },
      {
        "n": 1300000,
        "doi": "10.1016/j.cell.2021.04.021",
        "value": "3",
        "method": "scRNA-seq only (no electrophysiology)",
        "metric": "Number of Pvalb supertypes identified",
        "n_analyzed": "1300000",
        "ci_or_error": null,
        "text_access": "fulltext",
        "n_definition": "cells profiled",
        "scope_region": "isocortex and hippocampal formation",
        "study_system": "mouse isocortex and hippocampal formation",
        "taxonomic_level": "supertype (transcriptomic only)",
        "scope_population": "Pvalb subclass only",
        "value_source_sentence": "the Sst and Pvalb subclasses are divided into 11 and 3 supertypes, respectively.",
        "experimental_conditions": "10x scRNA-seq"
      },
      {
        "n": 0,
        "doi": "10.1038/s41467-020-20328-4",
        "value": "continuous",
        "method": "scRNA-seq with morphological identification",
        "metric": "Number of molecularly distinct PV types in hippocampus",
        "n_analyzed": null,
        "ci_or_error": null,
        "text_access": "fulltext",
        "n_definition": "morphologically identified PV interneurons",
        "scope_region": "hippocampus only",
        "study_system": "mouse hippocampus",
        "taxonomic_level": "continuous variation (no discrete types)",
        "scope_population": "PV interneurons only",
        "value_source_sentence": "we find high transcriptomic similarity among PV-INs, with few genes showing divergent expression between morphologically different types",
        "experimental_conditions": "scRNA-seq in morphologically identified cells"
      }
    ],
    "comparison_id": "pv-subtype-molecular-markers",
    "comparison_name": "Molecular markers distinguishing PV interneuron subtypes across studies",
    "comparison_type": "cross-study conflict",
    "what_it_reveals": "PV interneuron subtype resolution varies dramatically by method and brain region. Visual cortex Patch-seq identifies 7 Pvalb met-types. Isocortex-wide scRNA-seq resolves 3 supertypes. Hippocampal scRNA-seq with morphological identification finds continuous variation without discrete types. This reveals a tension between discrete classification and continuous variation.",
    "homogeneity_check": {
      "caveats": [
        "Different brain regions (visual cortex vs isocortex vs hippocampus)",
        "Different classification methods (Patch-seq multimodal vs transcriptomic only vs morphology-guided)",
        "Que et al. reports 'continuous' rather than a number of types",
        "Different sample sizes and sequencing depths"
      ],
      "n_definition_uniform": "false",
      "scope_region_uniform": "false",
      "taxonomic_level_uniform": "false",
      "scope_population_uniform": "true"
    },
    "suggested_plot_type": "grouped bar"
  },
  "section_id": "section_02_evidence_package",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV/blob/df9fc7e8d455b084152c9d713558dae0013cef21/evidence/section_02_evidence_package.json",
  "target_ref": "wiki_page:computationalreviewpv-02",
  "review_repo": "ComputationalReviewPV",
  "section_ref": "wiki_page:computationalreviewpv-02",
  "source_path": "evidence/section_02_evidence_package.json",
  "source_refs": [
    "paper:paper-pm-33186530",
    "paper:paper-4dfe44516146",
    "paper:paper-81b583f41ed6"
  ],
  "section_title": "Molecular Identity and Transcriptomic Taxonomy",
  "source_policy": {
    "mode": "public_source_pointer_with_short_context",
    "notes": [
      "Local review repositories are read-only inputs.",
      "SciDEX stores paper metadata, structured evidence, file pointers, and short citation contexts; it does not copy full review prose."
    ],
    "source_commit_sha": "df9fc7e8d455b084152c9d713558dae0013cef21",
    "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV"
  },
  "generation_status": "complete",
  "review_bundle_ref": "analysis_bundle:ab-e6261c8263e7",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV/blob/df9fc7e8d455b084152c9d713558dae0013cef21/evidence/section_02_evidence_package.json",
  "commit_sha": "df9fc7e8d455b084152c9d713558dae0013cef21",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV"
}