Tasic et al. (2016) used scRNA-seq to identify 49 transcriptomic cell types in…

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scope: mouse V1 cortex; SMART-seq scRNA-seq
claim_text: Tasic et al. (2016) used scRNA-seq to identify 49 transcriptomic cell types in adult mouse primary visual cortex (V1), including 23 GABAergic, 19 glutamatergic, and 7 non-neuronal types.
section_id: section_02
source_url: https://github.com/AllenNeuralDynamics/ComputationalReviewVIP/blob/95e761177f7d2ec565983d3307c14ec238f9677c/evidence/section_02_evidence_package.json
review_repo: ComputationalReviewVIP
section_ref: wiki_page:computationalreviewvip-02-classification
source_kind: review_finding
source_path: evidence/section_02_evidence_package.json
source_span: We classified 1,679 high-quality single cells with extensive characterization into 49 transcriptomic cell types in adult mouse primary visual cortex.
study_system: mouse V1 cortex; SMART-seq scRNA-seq
section_title: Molecular Identity and Transcriptomic Taxonomy
evidence_summary: Single-cell RNA-seq on 1,679 cells from adult mouse V1; clustered into 49 transcriptomic types: 23 GABAergic, 19 glutamatergic, 7 non-neuronal.
review_bundle_ref: analysis_bundle:ab-2ce40c33e827
replication_status: single_study
review_package_ref: analysis_bundle:ab-2ce40c33e827
source_artifact_ref: wiki_page:computationalreviewvip-02-classification
origin_url: https://github.com/AllenNeuralDynamics/ComputationalReviewVIP/blob/95e761177f7d2ec565983d3307c14ec238f9677c/evidence/section_02_evidence_package.json
commit_sha: 95e761177f7d2ec565983d3307c14ec238f9677c
created_by: persona-jerome-lecoq-gbo-neuroscience
repository_url: https://github.com/AllenNeuralDynamics/ComputationalReviewVIP

Raw fields (4)

raw_fields

{
  "n": 1679,
  "doi": "10.1038/nn.4216",
  "claim": "Tasic et al. (2016) used scRNA-seq to identify 49 transcriptomic cell types in adult mouse primary visual cortex (V1), including 23 GABAergic, 19 glutamatergic, and 7 non-neuronal types.",
  "title": null,
  "cite_key": "Tasic2016",
  "evidence": "Single-cell RNA-seq on 1,679 cells from adult mouse V1; clustered into 49 transcriptomic types: 23 GABAergic, 19 glutamatergic, 7 non-neuronal.",
  "effect_size": null,
  "text_access": "fulltext",
  "study_system": "mouse V1 cortex; SMART-seq scRNA-seq",
  "target_section": "section_02",
  "_source_cluster": "cluster_01_molecular_taxonomy",
  "replication_status": "single_study",
  "_source_cluster_index": 0,
  "claim_source_sentence": "We classified 1,679 high-quality single cells with extensive characterization into 49 transcriptomic cell types in adult mouse primary visual cortex."
}

source_refs

[
  "paper:paper-ed2a7f08ef35"
]

evidence_refs

[
  {
    "ref": "paper:paper-ed2a7f08ef35"
  }
]

source_policy

{
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  "notes": [
    "Local review repositories are read-only inputs.",
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  ],
  "source_commit_sha": "95e761177f7d2ec565983d3307c14ec238f9677c",
  "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewVIP"
}

Tasic et al. (2016) used scRNA-seq to identify 49 transcriptomic cell types in…

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