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Samuel L. Wolock

Researcher at Harvard University

Publications -  25
Citations -  4061

Samuel L. Wolock is an academic researcher from Harvard University. The author has contributed to research in topics: Population & Progenitor cell. The author has an hindex of 13, co-authored 25 publications receiving 2434 citations. Previous affiliations of Samuel L. Wolock include The Research Institute at Nationwide Children's Hospital & Nationwide Children's Hospital.

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A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure.

TL;DR: A droplet-based, single-cell RNA-seq method is implemented to determine the transcriptomes of over 12,000 individual pancreatic cells from four human donors and two mouse strains and provides a resource for the discovery of novel cell type-specific transcription factors, signaling receptors, and medically relevant genes.
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Scrublet: Computational Identification of Cell Doublets in Single-Cell Transcriptomic Data.

TL;DR: Scrublet avoids the need for expert knowledge or cell clustering by simulating multiplets from the data and building a nearest neighbor classifier, a framework for predicting the impact of multiplets in a given analysis and identifying problematic multiplets.
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Clonal analysis of lineage fate in native haematopoiesis

TL;DR: This study provides evidence for a substantially revised roadmap for unperturbed haematopoiesis, and highlights unique properties of multipotent progenitors and haem atopoietic stem cells in situ.
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Population snapshots predict early haematopoietic and erythroid hierarchies

TL;DR: It is found that the cell cycle is progressively remodelled during erythroid development and during a sharp transcriptional switch that ends the colony-forming progenitor stage and activates terminal differentiation, and provides insights into lineage development in vivo.
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SPRING: a kinetic interface for visualizing high dimensional single-cell expression data.

TL;DR: SPRING is described, a pipeline for data filtering, normalization and visualization using force-directed layouts and it is shown that it reveals more detailed biological relationships than existing approaches when applied to branching gene expression trajectories from hematopoietic progenitor cells and cells of the upper airway epithelium.