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Research method

Single-cell RNA-seq (scRNA-seq)

Single-cell RNA-seq measures transcriptomes of individual cells so heterogeneous tissues, organoids, or tumors are not averaged into one bulk profile. In this library it appears in stem-cell differentiation, vascularized brain organoids, and a colorectal cancer atlas.

Students meet scRNA-seq as a magic atlas button. Real papers use it for different claims—lineage transitions, organoid cell states, or tumor/stroma stratification—that should stay separated.

Studies

4

Findings

4

4 supporting · 0 challenging · 4 qualifying citations

Open tensions

2

Currently

What we know

  1. scRNA-seq can separate definitive endoderm progenitors and point to hypoxia effects in hESC cultures.
  2. In vascularized cortical organoids, scRNA-seq tracks neurogenesis and vessel-related programs.
  3. A CRC single-cell atlas links CMS labels to immune/stromal states and outcomes.
  4. snRNA-seq maps end-stage ischemic cardiomyopathy cell states.

Largest unresolved question

hESC endoderm time courses, brain organoid atlases, and CRC tumor atlases all use scRNA-seq without answering the same biological question—do not average their findings into one ‘scRNA-seq result.’

Common misconceptions

  • scRNA-seq always yields one clean cell-type map that replaces bulk CMS or FACS markers.

    Atlases can show continua and intratumoral heterogeneity; CMS labels still appear as mixed states within tumors.

  • If a paper mentions scRNA-seq, it is automatically a good undergraduate study card on the method alone.

    Many high-citation ‘scRNA’ hits are software toolboxes; this page privileges empirical biology papers with clear findings.

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