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Cole Trapnell

Researcher at University of Washington

Publications -  148
Citations -  101469

Cole Trapnell is an academic researcher from University of Washington. The author has contributed to research in topics: Biology & Gene. The author has an hindex of 57, co-authored 123 publications receiving 84590 citations. Previous affiliations of Cole Trapnell include Iowa State University & Massachusetts Institute of Technology.

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Massively multiplex chemical transcriptomics at single-cell resolution

TL;DR: The results with histone deacetylase inhibitors support the view that chromatin acts as an important reservoir of acetate in cancer cells, and reveal substantial intercellular heterogeneity in response to specific compounds, commonalities inresponse to families of compounds, and insight into differential properties within families.
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Single-Cell Transcriptomic Comparison of Human Fetal Retina, hPSC-Derived Retinal Organoids, and Long-Term Retinal Cultures.

TL;DR: The authors' single-cell RNA sequencing comparisons of fetal retina, retinal organoids, and retinospheres provide a resource for developing better in vitro models for retinal disease.
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On the design of CRISPR-based single-cell molecular screens.

TL;DR: This work optimized a published alternative, CROP-seq, in which the guide RNA also serves as the barcode, and here confirm that this strategy performs robustly and doubled the rate at which guides are assigned to cells to 94%.
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A pooled single-cell genetic screen identifies regulatory checkpoints in the continuum of the epithelial-to-mesenchymal transition.

TL;DR: Inhibiting the KRAS effector MEK and its upstream activators EGFR and MET demonstrates that interruption of key signaling events reveals regulatory ‘checkpoints’ in the EMT continuum that mimic discrete stages, and reconciles opposing views of the program that controls EMT.
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Modeling and automation of sequencing-based characterization of RNA structure

TL;DR: A novel assay utilizing selective 2′-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq) that can be used to characterize RNA secondary and tertiary structure and is generalized to modeling polymerase drop-off in other sequence census-based experiments.